Displaying publications 81 - 100 of 735 in total

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  1. Fulltext Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm
    Al-Saffar A, Awang S, Tao H, Omar N, Al-Saiagh W, Al-Bared M
    PLoS One, 2018;13(4):e0194852.
    PMID: 29684036 DOI: 10.1371/journal.pone.0194852
    Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. In this paper, a Malay sentiment analysis classification model is proposed to improve classification performances based on the semantic orientation and machine learning approaches. First, a total of 2,478 Malay sentiment-lexicon phrases and words are assigned with a synonym and stored with the help of more than one Malay native speaker, and the polarity is manually allotted with a score. In addition, the supervised machine learning approaches and lexicon knowledge method are combined for Malay sentiment classification with evaluating thirteen features. Finally, three individual classifiers and a combined classifier are used to evaluate the classification accuracy. In experimental results, a wide-range of comparative experiments is conducted on a Malay Reviews Corpus (MRC), and it demonstrates that the feature extraction improves the performance of Malay sentiment analysis based on the combined classification. However, the results depend on three factors, the features, the number of features and the classification approach.
    Matched MeSH terms: Models, Theoretical
  2. Fulltext Development and validation of a mathematical model for ventilation rate in crop protection structures
    Al-Shamiry, Faisal Mohammed Seif, Desa Ahmad
    Pertanika Journal of Science & Technology, 2010;18(1):-.
    MyJurnal
    Natural ventilation is defined as the number of air exchanges per hour per unit floor area necessary
    to reduce high indoor air temperature and humidity. In addition, it maintains the concentration of carbon dioxide. Natural ventilation is preferred in mechanical system as the ventilation opening is built into the greenhouse, with lower construction cost and no energy and maintenance inputs are required. A mathematical model to quantify natural ventilation rates was developed and verified in large-scale greenhouse structures. For this purpose, four Naturally Ventilated Tropical Greenhouse Structures were designed and constructed at the Malaysian Agricultural Research and Development Institute (MARDI). These were single, double, triple, and quadruple span structures with floor areas of 500 m2, 1000 m2, 1500 m2 and 2000 m2, respectively. This paper presents the validation of a mathematical model which was developed to quantify natural ventilation rates which are very crucial to reduce high in-house temperature built up in the tropics. Regression equations of natural ventilation against wind speed were found to be Φw = 0.0632V, Φw= 0.0395V, Φw= 0.0316Vand Φw=0.0276V for the single, double, triple and quadruple spans, respectively. Meanwhile, coefficients of determination showed strong relationships between ventilation rate and wind speed, with R2 = 0.9999 for all structures. Larger floor area was found to have higher in-house temperature than smaller ones. Ventilation rate inside the single-span structure was found to be higher compared to the multi-span structures, which increased linearly with the increasing wind speed at the eaves of structure.
    Matched MeSH terms: Models, Theoretical
  3. Feasibility study of sequencing batch reactor system for upgrading wastewater treatment in Malaysia
    Al-Shididi S, Henze M, Ujang Z
    Water Sci Technol, 2003;48(11-12):327-35.
    PMID: 14753553
    The objective of this study was to assess the feasibility of the Sequencing Batch Reactor (SBR) system for implementation in Malaysia. Theoretical, field, laboratory investigations, and modelling simulations have been carried out. The results of the study indicated that the SBR system was robust, relatively cost-effective, and efficient under Malaysian conditions. However, the SBR system requires highly skilled operators and continuous monitoring. This paper also attempted to identify operating conditions for the SBR system, which optimise both the removal efficiencies and the removal rates. The removal efficiencies could reach 90-96% for COD, up to 92% for TN, and 95% for SS. An approach to estimate a full operational cycle time, to estimate the de-sludging rate, and to control the biomass in the sludge has also been developed. About 4 hours react time was obtained, as 2.25 hours of nitrification with aerated slow fill and 1.75 hour of denitrification with HAc addition as an additional carbon source. Inefficient settling was one of the problems that affect the SBR effluent quality. The settling time was one hour for achieving Standard B (effluent quality) and 2 hours for Standard A.
    Matched MeSH terms: Models, Theoretical*
  4. Allyl triphenyl phosphonium bromide based DES-functionalized carbon nanotubes for the removal of mercury from water
    AlOmar MK, Alsaadi MA, Hayyan M, Akib S, Ibrahim M, Hashim MA
    Chemosphere, 2017 Jan;167:44-52.
    PMID: 27710842 DOI: 10.1016/j.chemosphere.2016.09.133
    Recently, deep eutectic solvents (DESs) have shown their new and interesting ability for chemistry through their involvement in variety of applications. This study introduces carbon nanotubes (CNTs) functionalized with DES as a novel adsorbent for Hg(2+) from water. Allyl triphenyl phosphonium bromide (ATPB) was combined with glycerol as the hydrogen bond donor (HBD) to form DES, which can act as a novel CNTs functionalization agent. The novel adsorbent was characterized using Raman, FTIR, XRD, FESEM, EDX, BET surface area, TGA, TEM and Zeta potential. Response surface methodology was used to optimize the removal conditions for Hg(2+). The optimum removal conditions were found to be pH 5.5, contact time 28 min, and an adsorbent dosage of 5 mg. Freundlich isotherm model described the adsorption isotherm of the novel adsorbent, and the maximum adsorption capacity obtained from the experimental data was 186.97 mg g(-1). Pseudo-second order kinetics describes the adsorption rate order.
    Matched MeSH terms: Models, Theoretical
  5. Fulltext Review of Recent Microwave Planar Resonator-Based Sensors: Techniques of Complex Permittivity Extraction, Applications, Open Challenges and Future Research Directions
    Alahnomi RA, Zakaria Z, Yussof ZM, Althuwayb AA, Alhegazi A, Alsariera H, et al.
    Sensors (Basel), 2021 Mar 24;21(7).
    PMID: 33804904 DOI: 10.3390/s21072267
    Recent developments in the field of microwave planar sensors have led to a renewed interest in industrial, chemical, biological and medical applications that are capable of performing real-time and non-invasive measurement of material properties. Among the plausible advantages of microwave planar sensors is that they have a compact size, a low cost and the ease of fabrication and integration compared to prevailing sensors. However, some of their main drawbacks can be considered that restrict their usage and limit the range of applications such as their sensitivity and selectivity. The development of high-sensitivity microwave planar sensors is required for highly accurate complex permittivity measurements to monitor the small variations among different material samples. Therefore, the purpose of this paper is to review recent research on the development of microwave planar sensors and further challenges of their sensitivity and selectivity. Furthermore, the techniques of the complex permittivity extraction (real and imaginary parts) are discussed based on the different approaches of mathematical models. The outcomes of this review may facilitate improvements of and an alternative solution for the enhancement of microwave planar sensors' normalized sensitivity for material characterization, especially in biochemical and beverage industry applications.
    Matched MeSH terms: Models, Theoretical
  6. Fulltext A robust fuzzy logic-based model for predicting the critical total drawdown in sand production in oil and gas wells
    Alakbari FS, Mohyaldinn ME, Ayoub MA, Muhsan AS, Hussein IA
    PLoS One, 2021;16(4):e0250466.
    PMID: 33901240 DOI: 10.1371/journal.pone.0250466
    Sand management is essential for enhancing the production in oil and gas reservoirs. The critical total drawdown (CTD) is used as a reliable indicator of the onset of sand production; hence, its accurate prediction is very important. There are many published CTD prediction correlations in literature. However, the accuracy of most of these models is questionable. Therefore, further improvement in CTD prediction is needed for more effective and successful sand control. This article presents a robust and accurate fuzzy logic (FL) model for predicting the CTD. Literature on 23 wells of the North Adriatic Sea was used to develop the model. The used data were split into 70% training sets and 30% testing sets. Trend analysis was conducted to verify that the developed model follows the correct physical behavior trends of the input parameters. Some statistical analyses were performed to check the model's reliability and accuracy as compared to the published correlations. The results demonstrated that the proposed FL model substantially outperforms the current published correlations and shows higher prediction accuracy. These results were verified using the highest correlation coefficient, the lowest average absolute percent relative error (AAPRE), the lowest maximum error (max. AAPRE), the lowest standard deviation (SD), and the lowest root mean square error (RMSE). Results showed that the lowest AAPRE is 8.6%, whereas the highest correlation coefficient is 0.9947. These values of AAPRE (<10%) indicate that the FL model could predicts the CTD more accurately than other published models (>20% AAPRE). Moreover, further analysis indicated the robustness of the FL model, because it follows the trends of all physical parameters affecting the CTD.
    Matched MeSH terms: Models, Theoretical*
  7. Fulltext Dynamics of fractional order nonlinear system: A realistic perception with neutrosophic fuzzy number and Allee effect
    Alam Khan N, Abdul Razzaq O, Riaz F, Ahmadian A, Senu N
    J Adv Res, 2021 09;32:109-118.
    PMID: 34484830 DOI: 10.1016/j.jare.2020.11.015
    Introduction: The fusion of fractional order differential equations and fuzzy numbers has been widely used in modelling different engineering and applied sciences problems. In addition to these, the Allee effect, which is of high importance in field of biology and ecology, has also shown great contribution among other fields of sciences to study the correlation between density and the mean fitness of the subject.

    Objectives: The present paper is intended to measure uncertain dynamics of an economy by restructuring the Cobb-Douglas paradigm of the renowned Solow-Swan model. The purpose of study is further boosted innovatively by subsuming the perception of logistic growth with Allee effect in the dynamics of physical capital and labor force.

    Methods: Fractional order derivative and neutrosophic fuzzy (NF) theory are applied on the parameters of the Cobb-Douglas equation. Distinctively, cogitating fractional order derivative to study the change at each fractional stage; single-valued triangular neutrosophic fuzzy numbers (SVTNFN) to cope the uncertain situations; logistic growth function with Allee effect to analyze the factors in natural way, are the significant and novel features of this endeavor.

    Results: The incorporation of the aforementioned theories and effects in the Cobb-Douglas equation, resulted in producing maximum sustainable capital investment and maximum capacity of labor force. The solutions in intervals located different possible solutions for different membership degrees, which accumulated the uncertain circumstances of a country.

    Conclusion: Explicitly, these notions add new facts and figures not only in the dynamical study of capital and labor, which has been overlooked in classical models, but also left the door open for discussion and implementation on classical models of different fields.

    Matched MeSH terms: Models, Theoretical
  8. A Critical Review for Developing Accurate and Dynamic Predictive Models Using Machine Learning Methods in Medicine and Health Care
    Alanazi HO, Abdullah AH, Qureshi KN
    J Med Syst, 2017 Apr;41(4):69.
    PMID: 28285459 DOI: 10.1007/s10916-017-0715-6
    Recently, Artificial Intelligence (AI) has been used widely in medicine and health care sector. In machine learning, the classification or prediction is a major field of AI. Today, the study of existing predictive models based on machine learning methods is extremely active. Doctors need accurate predictions for the outcomes of their patients' diseases. In addition, for accurate predictions, timing is another significant factor that influences treatment decisions. In this paper, existing predictive models in medicine and health care have critically reviewed. Furthermore, the most famous machine learning methods have explained, and the confusion between a statistical approach and machine learning has clarified. A review of related literature reveals that the predictions of existing predictive models differ even when the same dataset is used. Therefore, existing predictive models are essential, and current methods must be improved.
    Matched MeSH terms: Models, Theoretical*
  9. Fulltext Spoken language identification based on the enhanced self-adjusting extreme learning machine approach
    Albadr MAA, Tiun S, Al-Dhief FT, Sammour MAM
    PLoS One, 2018;13(4):e0194770.
    PMID: 29672546 DOI: 10.1371/journal.pone.0194770
    Spoken Language Identification (LID) is the process of determining and classifying natural language from a given content and dataset. Typically, data must be processed to extract useful features to perform LID. The extracting features for LID, based on literature, is a mature process where the standard features for LID have already been developed using Mel-Frequency Cepstral Coefficients (MFCC), Shifted Delta Cepstral (SDC), the Gaussian Mixture Model (GMM) and ending with the i-vector based framework. However, the process of learning based on extract features remains to be improved (i.e. optimised) to capture all embedded knowledge on the extracted features. The Extreme Learning Machine (ELM) is an effective learning model used to perform classification and regression analysis and is extremely useful to train a single hidden layer neural network. Nevertheless, the learning process of this model is not entirely effective (i.e. optimised) due to the random selection of weights within the input hidden layer. In this study, the ELM is selected as a learning model for LID based on standard feature extraction. One of the optimisation approaches of ELM, the Self-Adjusting Extreme Learning Machine (SA-ELM) is selected as the benchmark and improved by altering the selection phase of the optimisation process. The selection process is performed incorporating both the Split-Ratio and K-Tournament methods, the improved SA-ELM is named Enhanced Self-Adjusting Extreme Learning Machine (ESA-ELM). The results are generated based on LID with the datasets created from eight different languages. The results of the study showed excellent superiority relating to the performance of the Enhanced Self-Adjusting Extreme Learning Machine LID (ESA-ELM LID) compared with the SA-ELM LID, with ESA-ELM LID achieving an accuracy of 96.25%, as compared to the accuracy of SA-ELM LID of only 95.00%.
    Matched MeSH terms: Models, Theoretical
  10. Fulltext Coverage extension and balancing the transmitted power of the moving relay node at LTE-A cellular network
    Aldhaibani JA, Yahya A, Ahmad RB
    ScientificWorldJournal, 2014;2014:815720.
    PMID: 24672378 DOI: 10.1155/2014/815720
    The poor capacity at cell boundaries is not enough to meet the growing demand and stringent design which required high capacity and throughput irrespective of user's location in the cellular network. In this paper, we propose new schemes for an optimum fixed relay node (RN) placement in LTE-A cellular network to enhance throughput and coverage extension at cell edge region. The proposed approach mitigates interferences between all nodes and ensures optimum utilization with the optimization of transmitted power. Moreover, we proposed a new algorithm to balance the transmitted power of moving relay node (MR) over cell size and providing required SNR and throughput at the users inside vehicle along with reducing the transmitted power consumption by MR. The numerical analysis along with the simulation results indicates that an improvement in capacity for users is 40% increment at downlink transmission from cell capacity. Furthermore, the results revealed that there is saving nearly 75% from transmitted power in MR after using proposed balancing algorithm. ATDI simulator was used to verify the numerical results, which deals with real digital cartographic and standard formats for terrain.
    Matched MeSH terms: Models, Theoretical
  11. A novel mechanism measurement of predator interference in predator-prey models
    Alebraheem J, Abu-Hassan Y
    J Math Biol, 2023 Apr 27;86(5):84.
    PMID: 37103566 DOI: 10.1007/s00285-023-01914-8
    A characteristic of ecosystems is the existence of manifold of independencies which are highly complex. Various mathematical models have made considerable contributions in gaining a better understanding of the predator-prey interactions. The main components of any predator-prey models are, firstly, how the different population classes grow and secondly, how the prey and predator interacts. In this paper, the two populations' growth rates obey the logistic law and the carrying capacity of the predator depends on the available number of prey are considered. Our aim is to clarify the relationship between models and Holling types functional and numerical responses in order to gain insights into predator interferences and to answer an important question how competition is carried out. We consider a predator-prey model and a two-predator one-prey model to explain the idea. The novel approach is explained for the mechanism measurement of predator interference through depending on numerical response. Our approach gives good correspondence between an important real data and computer simulations.
    Matched MeSH terms: Models, Theoretical
  12. Fulltext Turbulence model sensitivity and scour gap effect of unsteady flow around pipe: a CFD study
    Ali A, Sharma RK, Ganesan P, Akib S
    ScientificWorldJournal, 2014;2014:412136.
    PMID: 25136666 DOI: 10.1155/2014/412136
    A numerical investigation of incompressible and transient flow around circular pipe has been carried out at different five gap phases. Flow equations such as Navier-Stokes and continuity equations have been solved using finite volume method. Unsteady horizontal velocity and kinetic energy square root profiles are plotted using different turbulence models and their sensitivity is checked against published experimental results. Flow parameters such as horizontal velocity under pipe, pressure coefficient, wall shear stress, drag coefficient, and lift coefficient are studied and presented graphically to investigate the flow behavior around an immovable pipe and scoured bed.
    Matched MeSH terms: Models, Theoretical*
  13. Fulltext A metamodel for mobile forensics investigation domain
    Ali A, Abd Razak S, Othman SH, Mohammed A, Saeed F
    PLoS One, 2017;12(4):e0176223.
    PMID: 28445486 DOI: 10.1371/journal.pone.0176223
    With the rapid development of technology, mobile phones have become an essential tool in terms of crime fighting and criminal investigation. However, many mobile forensics investigators face difficulties with the investigation process in their domain. These difficulties are due to the heavy reliance of the forensics field on knowledge which, although a valuable resource, is scattered and widely dispersed. The wide dispersion of mobile forensics knowledge not only makes investigation difficult for new investigators, resulting in substantial waste of time, but also leads to ambiguity in the concepts and terminologies of the mobile forensics domain. This paper developed an approach for mobile forensics domain based on metamodeling. The developed approach contributes to identify common concepts of mobile forensics through a development of the Mobile Forensics Metamodel (MFM). In addion, it contributes to simplifying the investigation process and enables investigation teams to capture and reuse specialized forensic knowledge, thereby supporting the training and knowledge management activities. Furthermore, it reduces the difficulty and ambiguity in the mobile forensics domain. A validation process was performed to ensure the completeness and correctness of the MFM. The validation was conducted using two techniques for improvements and adjustments to the metamodel. The last version of the adjusted metamodel was named MFM 1.2.
    Matched MeSH terms: Models, Theoretical*
  14. Fulltext Conjugate effects of heat and mass transfer on MHD free convection flow over an inclined plate embedded in a porous medium
    Ali F, Khan I, Samiulhaq, Shafie S
    PLoS One, 2013;8(6):e65223.
    PMID: 23840321 DOI: 10.1371/journal.pone.0065223
    The aim of this study is to present an exact analysis of combined effects of radiation and chemical reaction on the magnetohydrodynamic (MHD) free convection flow of an electrically conducting incompressible viscous fluid over an inclined plate embedded in a porous medium. The impulsively started plate with variable temperature and mass diffusion is considered. The dimensionless momentum equation coupled with the energy and mass diffusion equations are analytically solved using the Laplace transform method. Expressions for velocity, temperature and concentration fields are obtained. They satisfy all imposed initial and boundary conditions and can be reduced, as special cases, to some known solutions from the literature. Expressions for skin friction, Nusselt number and Sherwood number are also obtained. Finally, the effects of pertinent parameters on velocity, temperature and concentration profiles are graphically displayed whereas the variations in skin friction, Nusselt number and Sherwood number are shown through tables.
    Matched MeSH terms: Models, Theoretical
  15. Operating Rooms Scheduling for Elective Surgeries in a Hospital Affected by War-Related Incidents
    Ali HH, Lamsali H, Othman SN
    J Med Syst, 2019 Apr 10;43(5):139.
    PMID: 30972511 DOI: 10.1007/s10916-019-1263-z
    Hospital scheduling presents huge challenges for the healthcare industry. Various studies have been conducted in many different countries with focus on both elective and non-elective surgeries. There are important variables and factors that need to be taken into considerations. Different methods and approaches have also been used to examine hospital scheduling. Notwithstanding the continuous changes in modern healthcare services and, in particular, hospital operations, consistent reviews and further studies are still required. The importance of hospital scheduling, particularly, has become more critical as the trade-off between limited resources and overwhelming demand is becoming more evident. This situation is even more pressing in a volatile country where shootings and bombings in public areas happened. Hospital scheduling for elective surgeries in volatile country such as Iraq is therefore often interrupted by non-elective surgeries due to war-related incidents. Hence, this paper intends to address this issue by proposing a hospital scheduling model with focus on neuro-surgery department. The aim of the model is to maximize utilization of operating room while concurrently minimizing idle time of surgery. The study focused on neurosurgery department in Al-Shahid Ghazi Al-Hariri hospital in Baghdad, Iraq. In doing so, a Mixed-integer linear programming (MILP) model is formulated where interruptions of non-elective surgery are incorporated into the main elective surgery based model. Computational experiment is then carried out to test the model. The result indicates that the model is feasible and can be solved in reasonable times. Nonetheless, its feasibility is further tested as the problems size and the computation times is getting bigger and longer. Application of heuristic methods is the way forward to ensure better practicality of the proposed model. In the end, the potential benefit of this study and the proposed model is discussed.
    Matched MeSH terms: Models, Theoretical
  16. Osteoblasts infill irregular pores under curvature and porosity controls: a hypothesis-testing analysis of cell behaviours
    Alias MA, Buenzli PR
    Biomech Model Mechanobiol, 2018 Oct;17(5):1357-1371.
    PMID: 29846824 DOI: 10.1007/s10237-018-1031-x
    The geometric control of bone tissue growth plays a significant role in bone remodelling, age-related bone loss, and tissue engineering. However, how exactly geometry influences the behaviour of bone-forming cells remains elusive. Geometry modulates cell populations collectively through the evolving space available to the cells, but it may also modulate the individual behaviours of cells. To factor out the collective influence of geometry and gain access to the geometric regulation of individual cell behaviours, we develop a mathematical model of the infilling of cortical bone pores and use it with available experimental data on cortical infilling rates. Testing different possible modes of geometric controls of individual cell behaviours consistent with the experimental data, we find that efficient smoothing of irregular pores only occurs when cell secretory rate is controlled by porosity rather than curvature. This porosity control suggests the convergence of a large scale of intercellular signalling to single bone-forming cells, consistent with that provided by the osteocyte network in response to mechanical stimulus. After validating the mathematical model with the histological record of a real cortical pore infilling, we explore the infilling of a population of randomly generated initial pore shapes. We find that amongst all the geometric regulations considered, the collective influence of curvature on cell crowding is a dominant factor for how fast cortical bone pores infill, and we suggest that the irregularity of cement lines thereby explains some of the variability in double labelling data as well as the overall speed of osteon infilling.
    Matched MeSH terms: Models, Theoretical
  17. Fulltext Chronology of DIC technique based on the fundamental mathematical modeling and dehydration impact
    Alias N, Saipol HF, Ghani AC
    J Food Sci Technol, 2014 Dec;51(12):3647-57.
    PMID: 25477631 DOI: 10.1007/s13197-012-0913-7
    A chronology of mathematical models for heat and mass transfer equation is proposed for the prediction of moisture and temperature behavior during drying using DIC (Détente Instantanée Contrôlée) or instant controlled pressure drop technique. DIC technique has the potential as most commonly used dehydration method for high impact food value including the nutrition maintenance and the best possible quality for food storage. The model is governed by the regression model, followed by 2D Fick's and Fourier's parabolic equation and 2D elliptic-parabolic equation in a rectangular slice. The models neglect the effect of shrinkage and radiation effects. The simulations of heat and mass transfer equations with parabolic and elliptic-parabolic types through some numerical methods based on finite difference method (FDM) have been illustrated. Intel®Core™2Duo processors with Linux operating system and C programming language have been considered as a computational platform for the simulation. Qualitative and quantitative differences between DIC technique and the conventional drying methods have been shown as a comparative.
    Matched MeSH terms: Models, Theoretical
  18. Fulltext Determination of important topographic factors for landslide mapping analysis using MLP network
    Alkhasawneh MSh, Ngah UK, Tay LT, Mat Isa NA, Al-batah MS
    ScientificWorldJournal, 2013;2013:415023.
    PMID: 24453846 DOI: 10.1155/2013/415023
    Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.
    Matched MeSH terms: Models, Theoretical*
  19. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models
    Allawi MF, Jaafar O, Mohamad Hamzah F, Abdullah SMS, El-Shafie A
    Environ Sci Pollut Res Int, 2018 May;25(14):13446-13469.
    PMID: 29616480 DOI: 10.1007/s11356-018-1867-8
    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.
    Matched MeSH terms: Models, Theoretical
  20. Fulltext Analysis of feeder bus network design and scheduling problems
    Almasi MH, Mirzapour Mounes S, Koting S, Karim MR
    ScientificWorldJournal, 2014;2014:408473.
    PMID: 24526890 DOI: 10.1155/2014/408473
    A growing concern for public transit is its inability to shift passenger's mode from private to public transport. In order to overcome this problem, a more developed feeder bus network and matched schedules will play important roles. The present paper aims to review some of the studies performed on Feeder Bus Network Design and Scheduling Problem (FNDSP) based on three distinctive parts of the FNDSP setup, namely, problem description, problem characteristics, and solution approaches. The problems consist of different subproblems including data preparation, feeder bus network design, route generation, and feeder bus scheduling. Subsequently, descriptive analysis and classification of previous works are presented to highlight the main characteristics and solution methods. Finally, some of the issues and trends for future research are identified. This paper is targeted at dealing with the FNDSP to exhibit strategic and tactical goals and also contributes to the unification of the field which might be a useful complement to the few existing reviews.
    Matched MeSH terms: Models, Theoretical*
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