Displaying publications 1 - 20 of 69 in total

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  1. Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system
    Hannan MA, Arebey M, Begum RA, Basri H
    Waste Manag, 2011 Dec;31(12):2406-13.
    PMID: 21871788 DOI: 10.1016/j.wasman.2011.07.022
    This paper deals with a system of integration of Radio Frequency Identification (RFID) and communication technologies for solid waste bin and truck monitoring system. RFID, GPS, GPRS and GIS along with camera technologies have been integrated and developed the bin and truck intelligent monitoring system. A new kind of integrated theoretical framework, hardware architecture and interface algorithm has been introduced between the technologies for the successful implementation of the proposed system. In this system, bin and truck database have been developed such a way that the information of bin and truck ID, date and time of waste collection, bin status, amount of waste and bin and truck GPS coordinates etc. are complied and stored for monitoring and management activities. The results showed that the real-time image processing, histogram analysis, waste estimation and other bin information have been displayed in the GUI of the monitoring system. The real-time test and experimental results showed that the performance of the developed system was stable and satisfied the monitoring system with high practicability and validity.
    Matched MeSH terms: Computer Systems/economics*
  2. Fulltext TECHNO-ECONOMIC FEASIBILITY STUDY OF AN OFF-GRID HYBRID POWER SYSTEM FOR AN AQUA-TOURISM RESORT IN TERENGGANU, MALAYSIA
    MUHAMMAD FAKHRURAZI MD YUNOS, NUR FARIZAN MUNAJAT, WAN MARIAM WAN MUDA
    UMT Journal of Undergraduate Research, 2019;1(2):103-110.
    MyJurnal
    This study focused on feasibility analysis of hybrid electrification system for an aqua-tourism resort located remotely from the grid connection in Terengganu. There were four standalone systems used in this study: diesel/PV/biomass/battery, diesel/PV/battery, biomass/diesel/battery, and diesel only. The design and analysis of these systems were done using Hybrid Optimization of MultipleEnergy Resources (HOMER) software. The results showed that the diesel/PV/battery system was the optimum solution in terms of net present cost (NPC) and cost of energy (COE). This system comprises 20 % of PV penetration with NPC and COE of USD 57,823 (RM 241, 729.90) and 0.428 USD/kWh (1.79 RM/kWh), respectively. Meanwhile, the diesel/PV/biomass/battery system with NPC of USD 65,388 (RM 273, 355.49) and COE of 0.484 USD/kWh (2.02 RM/kWh) was found to be the best among all systems in terms of greenhouse emissions. This system was able to reduce almost 70 % of carbon dioxide if compared with diesel only system and about 15 % lower than the diesel/PV/battery system with a renewable energy fraction of 44 %.
    Matched MeSH terms: Computer Systems
  3. Fulltext ESTIMATION OF SAND DISTRIBUTION IN CORAL REEF ENVIRONMENT USING COLOURSEGMENTATION AND COLOURTHRESHOLDING METHODS
    PAULEEN ONG, MUHAMMAD SUZURI HITAM, ZAINUDDIN BACHOK, ZAINUDDIN BACHOK, MOHD SAFUAN CHE DIN
    UMT Journal of Undergraduate Research, 2019;1(3):96-104.
    MyJurnal
    At present, marine scientists employ manual method to estimate the components in coral reef environment,where Coral Point Count with Excel extensions (CPCe) software is used to determine the coral reef components and substrate coverage. This manual processis laboriousand time consuming,and needsexpertsto conduct the survey. In this paper, a prototype for estimating the distribution of sand cover in coral reef environment from still images by using colourextraction methods was introduced. The coloursegmentation called delta E was used to calculate the colourdifference between two coloursamples. Another method used wascolourthresholdby setting the range of sand colourpixels. Thesystem was developed by using a MATLAB software withimage processing toolbox. The developed system was semi-automatic computer-based system that can be used by researcherseven with little knowledge and experience to estimatethepercentage of sand coveragein coral reef still images.
    Matched MeSH terms: Computer Systems
  4. Fulltext Minimizing thermal stress for data center servers through thermal-aware relocation
    Chaudhry MT, Ling TC, Hussain SA, Manzoor A
    ScientificWorldJournal, 2014;2014:684501.
    PMID: 24987743 DOI: 10.1155/2014/684501
    A rise in inlet air temperature may lower the rate of heat dissipation from air cooled computing servers. This introduces a thermal stress to these servers. As a result, the poorly cooled active servers will start conducting heat to the neighboring servers and giving rise to hotspot regions of thermal stress, inside the data center. As a result, the physical hardware of these servers may fail, thus causing performance loss, monetary loss, and higher energy consumption for cooling mechanism. In order to minimize these situations, this paper performs the profiling of inlet temperature sensitivity (ITS) and defines the optimum location for each server to minimize the chances of creating a thermal hotspot and thermal stress. Based upon novel ITS analysis, a thermal state monitoring and server relocation algorithm for data centers is being proposed. The contribution of this paper is bringing the peak outlet temperatures of the relocated servers closer to average outlet temperature by over 5 times, lowering the average peak outlet temperature by 3.5% and minimizing the thermal stress.
    Matched MeSH terms: Computer Systems*
  5. Fulltext A new sensors-based covert channel on android
    Al-Haiqi A, Ismail M, Nordin R
    ScientificWorldJournal, 2014;2014:969628.
    PMID: 25295311 DOI: 10.1155/2014/969628
    Covert channels are not new in computing systems, and have been studied since their first definition four decades ago. New platforms invoke thorough investigations to assess their security. Now is the time for Android platform to analyze its security model, in particular the two key principles: process-isolation and the permissions system. Aside from all sorts of malware, one threat proved intractable by current protection solutions, that is, collusion attacks involving two applications communicating over covert channels. Still no universal solution can countermeasure this sort of attack unless the covert channels are known. This paper is an attempt to reveal a new covert channel, not only being specific to smartphones, but also exploiting an unusual resource as a vehicle to carry covert information: sensors data. Accelerometers generate signals that reflect user motions, and malware applications can apparently only read their data. However, if the vibration motor on the device is used properly, programmatically produced vibration patterns can encode stolen data and hence an application can cause discernible effects on acceleration data to be received and decoded by another application. Our evaluations confirmed a real threat where strings of tens of characters could be transmitted errorless if the throughput is reduced to around 2.5-5 bps. The proposed covert channel is very stealthy as no unusual permissions are required and there is no explicit communication between the colluding applications.
    Matched MeSH terms: Computer Systems/trends
  6. Fulltext Analysis of motorcyclist riding behaviour on speed table
    Yuen CW, Karim MR, Saifizul A
    ScientificWorldJournal, 2014;2014:236396.
    PMID: 24991638 DOI: 10.1155/2014/236396
    This paper focuses on the study of the change of various types of riding behaviour, such as speed, brake force, and throttle force applied, when they ride across the speed table. An instrumented motorcycle equipped with various types of sensor, on-board camera, and data logger was used in acquiring the traffic data in the research. Riders were instructed to ride across two speed tables and the riding data were then analyzed to study the behaviour change from different riders. The results from statistical analysis showed that the riding characteristics such as speed, brake force, and throttle force applied are influenced by distance from hump, riding experience, and travel mileage of riders. Riders tend to apply higher brake intensity at distance point 50 m before the speed table and release the braking at point -10 m after the hump. In short, speed table has different rates of influence towards riding behaviour on different factors, such as distance from hump and different riders' attributes.
    Matched MeSH terms: Computer Systems*
  7. Fulltext A comprehensive review on adaptability of network forensics frameworks for mobile cloud computing
    Khan S, Shiraz M, Wahab AW, Gani A, Han Q, Rahman ZB
    ScientificWorldJournal, 2014;2014:547062.
    PMID: 25097880 DOI: 10.1155/2014/547062
    Network forensics enables investigation and identification of network attacks through the retrieved digital content. The proliferation of smartphones and the cost-effective universal data access through cloud has made Mobile Cloud Computing (MCC) a congenital target for network attacks. However, confines in carrying out forensics in MCC is interrelated with the autonomous cloud hosting companies and their policies for restricted access to the digital content in the back-end cloud platforms. It implies that existing Network Forensic Frameworks (NFFs) have limited impact in the MCC paradigm. To this end, we qualitatively analyze the adaptability of existing NFFs when applied to the MCC. Explicitly, the fundamental mechanisms of NFFs are highlighted and then analyzed using the most relevant parameters. A classification is proposed to help understand the anatomy of existing NFFs. Subsequently, a comparison is given that explores the functional similarities and deviations among NFFs. The paper concludes by discussing research challenges for progressive network forensics in MCC.
    Matched MeSH terms: Computer Systems*
  8. Fulltext Comparison of Microtox and Xenoassay light as a near real time river monitoring assay for heavy metals
    Halmi MI, Jirangon H, Johari WL, Rachman AR, Shukor MY, Syed MA
    ScientificWorldJournal, 2014;2014:834202.
    PMID: 24977231 DOI: 10.1155/2014/834202
    Luminescence-based assays for toxicants such as Microtox, ToxAlert, and Biotox have been used extensively worldwide. However, the use of these assays in near real time conditions is limited due to nonoptimal assay temperature for the tropical climate. An isolate that exhibits a high luminescence activity in a broad range of temperatures was successfully isolated from the mackerel, Rastrelliger kanagurta. This isolate was tentatively identified as Photobacterium sp. strain MIE, based on partial 16S rDNA molecular phylogeny. Optimum conditions that support high bioluminescence activity occurred between 24 and 30°C, with pH 5.5 to 7.5, 10 to 20 g/L of sodium chloride, 30 to 50 g/L of tryptone, and 4 g/L of glycerol as the carbon source. Assessment of near real time capability of this bacterial system, Xenoassay light to monitor heavy metals from a contaminated river running through the Juru River Basin shows near real time capability with assaying time of less than 30 minutes per samples. Samples returned to the lab were tested with a standard Microtox assay using Vibrio fishceri. Similar results were obtained to Xenoassay light that show temporal variation of copper concentration. Thus, this strain is suitable for near real time river monitoring of toxicants especially in the tropics.
    Matched MeSH terms: Computer Systems
  9. Fulltext Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement
    Siswantoro J, Prabuwono AS, Abdullah A, Idrus B
    ScientificWorldJournal, 2014;2014:683048.
    PMID: 24892069 DOI: 10.1155/2014/683048
    Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.
    Matched MeSH terms: Computer Systems
  10. An Innovation-Driven Approach to Specific Language Impairment Diagnosis
    Ch'ng YH, Osman MA, Jong HY
    Malays J Med Sci, 2021 Apr;28(2):161-170.
    PMID: 33958970 DOI: 10.21315/mjms2021.28.2.15
    Background: Specific language impairment (SLI) diagnosis is inconvenient due to manual procedures and hardware cost. Computer-aided SLI diagnosis has been proposed to counter these inconveniences. This study focuses on evaluating the feasibility of computer systems used to diagnose SLI.

    Methods: The accuracy of Webgazer.js for software-based gaze tracking is tested under different lighting conditions. Predefined time delays of a prototype diagnosis task automation script are contrasted against with manual delays based on human time estimation to understand how automation influences diagnosis accuracy. SLI diagnosis binary classifier was built and tested based on randomised parameters. The obtained results were cross-compared to Singlims_ES.exe for equality.

    Results: Webgazer.js achieved an average accuracy of 88.755% under global lighting conditions, 61.379% under low lighting conditions and 52.7% under face-focused lighting conditions. The diagnosis task automation script found to execute with actual time delays with a deviation percentage no more than 0.04%, while manually executing time delays based on human time estimation resulted in a deviation percentage of not more than 3.37%. One-tailed test probability value produced by both the newly built classifier and Singlims_ES were observed to be similar up to three decimal places.

    Conclusion: The results obtained should serve as a foundation for further evaluation of computer tools to help speech language pathologists diagnose SLI.

    Matched MeSH terms: Computer Systems
  11. Objective assessment of vitiligo with a computerised digital imaging analysis system
    Shamsudin N, Hussein SH, Nugroho H, Fadzil MH
    Australas J Dermatol, 2015 Nov;56(4):285-9.
    PMID: 25367709 DOI: 10.1111/ajd.12247
    An objective tool to quantify treatment response in vitiligo is currently lacking. This study aimed to objectively evaluate the treatment response in vitiligo by using a computerised digital imaging analysis system (C-DIAS) and to compare it with the physician's global assessment (PGA). Tacrolimus ointment 0.1% (Protopic; Astellas Pharma Tech,Toyama, Japan) was applied twice daily on selected lesions which were photographed every 6 weeks for 24 weeks. The primary efficacy end-point was the mean percentage of repigmentation (MPR), as assessed by the digital method (MPR-C-DIAS) or by the PGA. The response was categorised into none (0%), mild (1-25%), moderate (26-50%), good (51-75%) and excellent (76-100%).
    Matched MeSH terms: Computer Systems
  12. Fulltext Dynamic electronic institutions in agent oriented cloud robotic systems
    Nagrath V, Morel O, Malik A, Saad N, Meriaudeau F
    Springerplus, 2015;4:103.
    PMID: 25763310 DOI: 10.1186/s40064-015-0810-4
    The dot-com bubble bursted in the year 2000 followed by a swift movement towards resource virtualization and cloud computing business model. Cloud computing emerged not as new form of computing or network technology but a mere remoulding of existing technologies to suit a new business model. Cloud robotics is understood as adaptation of cloud computing ideas for robotic applications. Current efforts in cloud robotics stress upon developing robots that utilize computing and service infrastructure of the cloud, without debating on the underlying business model. HTM5 is an OMG's MDA based Meta-model for agent oriented development of cloud robotic systems. The trade-view of HTM5 promotes peer-to-peer trade amongst software agents. HTM5 agents represent various cloud entities and implement their business logic on cloud interactions. Trade in a peer-to-peer cloud robotic system is based on relationships and contracts amongst several agent subsets. Electronic Institutions are associations of heterogeneous intelligent agents which interact with each other following predefined norms. In Dynamic Electronic Institutions, the process of formation, reformation and dissolution of institutions is automated leading to run time adaptations in groups of agents. DEIs in agent oriented cloud robotic ecosystems bring order and group intellect. This article presents DEI implementations through HTM5 methodology.
    Matched MeSH terms: Computer Systems
  13. Fulltext Performance Evaluation of Localization Accuracy for a Log-Normal Shadow Fading Wireless Sensor Network under Physical Barrier Attacks
    Hussein AA, Rahman TA, Leow CY
    Sensors (Basel), 2015;15(12):30545-70.
    PMID: 26690159 DOI: 10.3390/s151229817
    Localization is an apparent aspect of a wireless sensor network, which is the focus of much interesting research. One of the severe conditions that needs to be taken into consideration is localizing a mobile target through a dispersed sensor network in the presence of physical barrier attacks. These attacks confuse the localization process and cause location estimation errors. Range-based methods, like the received signal strength indication (RSSI), face the major influence of this kind of attack. This paper proposes a solution based on a combination of multi-frequency multi-power localization (C-MFMPL) and step function multi-frequency multi-power localization (SF-MFMPL), including the fingerprint matching technique and lateration, to provide a robust and accurate localization technique. In addition, this paper proposes a grid coloring algorithm to detect the signal hole map in the network, which refers to the attack-prone regions, in order to carry out corrective actions. The simulation results show the enhancement and robustness of RSS localization performance in the face of log normal shadow fading effects, besides the presence of physical barrier attacks, through detecting, filtering and eliminating the effect of these attacks.
    Matched MeSH terms: Computer Systems
  14. Fulltext Real-time gas identification by analyzing the transient response of capillary-attached conductive gas sensor
    Bahraminejad B, Basri S, Isa M, Hambli Z
    Sensors (Basel), 2010;10(6):5359-77.
    PMID: 22219666 DOI: 10.3390/s100605359
    In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.
    Matched MeSH terms: Computer Systems
  15. Fulltext System interface for an integrated intelligent safety system (ISS) for vehicle applications
    Hannan MA, Hussain A, Samad SA
    Sensors (Basel), 2010;10(2):1141-53.
    PMID: 22205861 DOI: 10.3390/s100201141
    This paper deals with the interface-relevant activity of a vehicle integrated intelligent safety system (ISS) that includes an airbag deployment decision system (ADDS) and a tire pressure monitoring system (TPMS). A program is developed in LabWindows/CVI, using C for prototype implementation. The prototype is primarily concerned with the interconnection between hardware objects such as a load cell, web camera, accelerometer, TPM tire module and receiver module, DAQ card, CPU card and a touch screen. Several safety subsystems, including image processing, weight sensing and crash detection systems, are integrated, and their outputs are combined to yield intelligent decisions regarding airbag deployment. The integrated safety system also monitors tire pressure and temperature. Testing and experimentation with this ISS suggests that the system is unique, robust, intelligent, and appropriate for in-vehicle applications.
    Matched MeSH terms: Computer Systems
  16. Fulltext Real-time curvature defect detection on outer surfaces using best-fit polynomial interpolation
    Golkar E, Prabuwono AS, Patel A
    Sensors (Basel), 2012;12(11):14774-91.
    PMID: 23202186 DOI: 10.3390/s121114774
    This paper presents a novel, real-time defect detection system, based on a best-fit polynomial interpolation, that inspects the conditions of outer surfaces. The defect detection system is an enhanced feature extraction method that employs this technique to inspect the flatness, waviness, blob, and curvature faults of these surfaces. The proposed method has been performed, tested, and validated on numerous pipes and ceramic tiles. The results illustrate that the physical defects such as abnormal, popped-up blobs are recognized completely, and that flames, waviness, and curvature faults are detected simultaneously.
    Matched MeSH terms: Computer Systems
  17. Fulltext A Vision-Based Machine Learning Method for Barrier Access Control Using Vehicle License Plate Authentication
    Islam KT, Raj RG, Shamsul Islam SM, Wijewickrema S, Hossain MS, Razmovski T, et al.
    Sensors (Basel), 2020 Jun 24;20(12).
    PMID: 32599883 DOI: 10.3390/s20123578
    Automatic vehicle license plate recognition is an essential part of intelligent vehicle access control and monitoring systems. With the increasing number of vehicles, it is important that an effective real-time system for automated license plate recognition is developed. Computer vision techniques are typically used for this task. However, it remains a challenging problem, as both high accuracy and low processing time are required in such a system. Here, we propose a method for license plate recognition that seeks to find a balance between these two requirements. The proposed method consists of two stages: detection and recognition. In the detection stage, the image is processed so that a region of interest is identified. In the recognition stage, features are extracted from the region of interest using the histogram of oriented gradients method. These features are then used to train an artificial neural network to identify characters in the license plate. Experimental results show that the proposed method achieves a high level of accuracy as well as low processing time when compared to existing methods, indicating that it is suitable for real-time applications.
    Matched MeSH terms: Computer Systems
  18. Fulltext A fuzzy controller for lower limb exoskeletons during sit-to-stand and stand-to-sit movement using wearable sensors
    Reza SM, Ahmad N, Choudhury IA, Ghazilla RA
    Sensors (Basel), 2014 Mar 04;14(3):4342-63.
    PMID: 24599193 DOI: 10.3390/s140304342
    Human motion is a daily and rhythmic activity. The exoskeleton concept is a very positive scientific approach for human rehabilitation in case of lower limb impairment. Although the exoskeleton shows potential, it is not yet applied extensively in clinical rehabilitation. In this research, a fuzzy based control algorithm is proposed for lower limb exoskeletons during sit-to-stand and stand-to-sit movements. Surface electromyograms (EMGs) are acquired from the vastus lateralis muscle using a wearable EMG sensor. The resultant acceleration angle along the z-axis is determined from a kinematics sensor. Twenty volunteers were chosen to perform the experiments. The whole experiment was accomplished in two phases. In the first phase, acceleration angles and EMG data were acquired from the volunteers during both sit-to-stand and stand-to-sit motions. During sit-to-stand movements, the average acceleration angle at activation was 11°-48° and the EMG varied from -0.19 mV to +0.19 mV. On the other hand, during stand-to-sit movements, the average acceleration angle was found to be 57.5°-108° at the activation point and the EMG varied from -0.32 mV to +0.32 mV. In the second phase, a fuzzy controller was designed from the experimental data. The controller was tested and validated with both offline and real time data using LabVIEW.
    Matched MeSH terms: Computer Systems
  19. Fulltext Spotted hyena optimizer algorithm for capacitor allocation in radial distribution system with distributed generation and microgrid operation considering different load types
    Naderipour A, Abdul-Malek Z, Hajivand M, Seifabad ZM, Farsi MA, Nowdeh SA, et al.
    Sci Rep, 2021 Feb 01;11(1):2728.
    PMID: 33526829 DOI: 10.1038/s41598-021-82440-9
    In this paper, the optimal allocation of constant and switchable capacitors is presented simultaneously in two operation modes, grid-connected and islanded, for a microgrid. Different load levels are considered by employing non-dispatchable distributed generations. The objective function includes minimising the energy losses cost, the cost of peak power losses, and the cost of the capacitor. The optimization problem is solved using the spotted hyena optimizer (SHO) algorithm to determine the optimal size and location of capacitors, considering different loading levels and the two operation modes. In this study, a three-level load and various types of loads, including constant power, constant current, and constant impedance are considered. The proposed method is implemented on a 24-bus radial distribution network. To evaluate the performance of the SHO, the results are compared with GWO and the genetic algorithm (GA). The simulation results demonstrate the superior performance of the SHO in reducing the cost of losses and improving the voltage profile during injection and non-injection of reactive power by distributed generations in two operation modes. The total cost and net saving values for DGs only with the capability of active power injection is achieved 105,780 $ and 100,560.54 $, respectively and for DGs with the capability of active and reactive power injection is obtained 89,568 $ and 76,850.46 $, respectively using the SHO. The proposed method has achieved more annual net savings due to the lower cost of losses than other optimization methods.
    Matched MeSH terms: Computer Systems
  20. Fulltext Short term energy consumption forecasting using neural basis expansion analysis for interpretable time series
    Shaikh AK, Nazir A, Khan I, Shah AS
    Sci Rep, 2022 Dec 29;12(1):22562.
    PMID: 36581655 DOI: 10.1038/s41598-022-26499-y
    Smart grids and smart homes are getting people's attention in the modern era of smart cities. The advancements of smart technologies and smart grids have created challenges related to energy efficiency and production according to the future demand of clients. Machine learning, specifically neural network-based methods, remained successful in energy consumption prediction, but still, there are gaps due to uncertainty in the data and limitations of the algorithms. Research published in the literature has used small datasets and profiles of primarily single users; therefore, models have difficulties when applied to large datasets with profiles of different customers. Thus, a smart grid environment requires a model that handles consumption data from thousands of customers. The proposed model enhances the newly introduced method of Neural Basis Expansion Analysis for interpretable Time Series (N-BEATS) with a big dataset of energy consumption of 169 customers. Further, to validate the results of the proposed model, a performance comparison has been carried out with the Long Short Term Memory (LSTM), Blocked LSTM, Gated Recurrent Units (GRU), Blocked GRU and Temporal Convolutional Network (TCN). The proposed interpretable model improves the prediction accuracy on the big dataset containing energy consumption profiles of multiple customers. Incorporating covariates into the model improved accuracy by learning past and future energy consumption patterns. Based on a large dataset, the proposed model performed better for daily, weekly, and monthly energy consumption predictions. The forecasting accuracy of the N-BEATS interpretable model for 1-day-ahead energy consumption with "day as covariates" remained better than the 1, 2, 3, and 4-week scenarios.
    Matched MeSH terms: Computer Systems*
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