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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark
Published 2021“…Parallel computing is demanded to allow for optimal resource utilization in dealing with smart grid big data. In this paper, a master-slave parallel computing paradigm is utilized and experimented with for load forecasting in a multi-AMI environment. …”
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Comparative analysis of metaheuristic load balancing algorithms for efficient load balancing in cloud computing
Published 2023“…This paper provides a comparative analysis of various metaheuristic load balancing algorithms for cloud computing based on performance factors i.e., Makespan time, degree of imbalance, response time, data center processing time, flow time, and resource utilization. …”
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LocationSpark: In-memory Distributed Spatial Query Processing and Optimization
Published 2020“…<p>Due to the ubiquity of spatial data applications and the large amounts of spatial data that these applications generate and process, there is a pressing need for scalable spatial query processing. …”
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A Multiprocessing-Based Sensitivity Analysis of Machine Learning Algorithms for Load Forecasting of Electric Power Distribution System
Published 2021“…The proliferation of smart meters in the grids has resulted in an explosion of energy datasets. Processing such data is challenging and usually takes a longer time than the requirement of a short-term load forecast. …”
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition
Published 2021“…<p>Different aggregation levels of the electric grid's big data can be helpful to develop highly accurate deep learning models for Short-term Load Forecasting (STLF) in electrical networks. …”
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Short-Term Load Forecasting in Active Distribution Networks Using Forgetting Factor Adaptive Extended Kalman Filter
Published 2023“…A few research studies focused on developing data filtering algorithm for the load forecasting process using approaches such as Kalman filter, which has good tracking capability in the presence of noise in the data collection process. …”
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Impact of urban morphology on urban microclimate and building energy loads
Published 2021“…With the help of the Urban Weather Generator (UWG) and a locally established weather station, this research explores the validity of UWG processed open weather data (i.e., World Weather Online and Open Weather Map datasets). …”
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Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…<div><p>Outpatient Chemotherapy Appointment (OCA) planning and scheduling is a process of distributing appointments to available days and times to be handled by various resources through a multi-stage process. …”
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Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model
Published 2021“…The proposed framework consists of two stages, namely, data cleaning, and model building. The data cleaning phase applies pre-processing techniques to the raw data and adds additional features of lag values. …”
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An intelligent nonintrusive load monitoring scheme based on 2D phase encoding of power signals
Published 2020“…<p dir="ltr">Nonintrusive load monitoring (NILM) is the de facto technique for extracting device-level power consumption fingerprints at (almost) no cost from only aggregated mains readings. …”
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Processing airborne LiDAR point cloud for solar cadasters: A review
Published 2025“…<p dir="ltr">This paper reviews existing literature in the critical role of processing Lidar point cloud data for generating Digital Elevation Models (DEMs)— Digital Surface Models (DSMs) and Digital Terrain Models (DTMs)—to develop solar cadasters, which are essential for optimizing solar energy deployment in urban environments. …”
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Time-constrained concurrent data-offloading in the cloud and fog
Published 2025“…<p dir="ltr">This paper discusses the concurrent offloading of data in a multi-platform configuration consisting of cloud and fog. devices feed these platforms with data that need to be stored, processed, and/or shared. …”
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Using big data safety analytics for proactive traffic management
Published 2015“…Real-time safety risk evaluation was developed for several expressways based on these data. Other big data applications involve combination of census, planning, safety, roadway and land use data to improve safety planning.…”
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Integrated Multi-Criteria Model for Long-Term Placement of Electric Vehicle Chargers
Published 2022“…These findings could also help administrators and policymakers make effective choices for future planning and strategy.</p><h2>Other Information</h2><p>Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/legalcode" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2022.3224796" target="_blank">https://dx.doi.org/10.1109/access.2022.3224796</a></p>…”
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Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. The effect of surface area loading rate (SALR), organic matters (OMs), nutrients (N & P), feed flow rate (Q<sub>feed</sub>), hydraulic retention time (HRT), and internal recycle flow (IRF) on the performance of the ENR-BP to fulfil rigorous discharge limitations were evaluated. …”
