The Utilization of a Naïve Bayes Model for Predicting the Energy Consumption of Buildings by Behnam Sadaghat, Ali Javadzade Khiavi, Babak Naeim, Erfan Khajavi, Hadi Sadaghat, Amir Reza Taghavi Khanghah

“…These algorithms are employed to improve HVAC system control, equipment sizing, energy management, and cost reduction. …”
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Optimal Allocation of Gas Supply Reliability in Natural Gas Pipeline System Based on Exterior Penalty Function Method by Yueqi LIU, Lei HOU, Shuaishuai TANG, Huai SU, Xingtao LI

“…Optimal allocation of gas supply reliability is an important part of gas supply reliability of natural gas pipeline system.In order to study the optimal allocation scheme of gas supply reliability with the lowest cost,a cost function model based on the gas supply capacity of the pipeline system was constructed.To address the limitation of traditional intelligent optimization algorithms (e.g.…”
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Quantum Marine Predator Algorithm: A Quantum Leap in Photovoltaic Efficiency Under Dynamic Conditions by Okba Fergani, Yassine Himeur, Raihane Mechgoug, Shadi Atalla, Wathiq Mansoor, Nacira Tkouti

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Behavior-aware energy management in microgrids using quantum-classical hybrid algorithms under social and demand dynamics by Liu Minghong, Fu Gaoshan, Wang Pengchao, Yuan Xin, Li Qing, Tengfei Hou, Zhang Shuo

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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…Abstract The purpose of this study was to model and optimize the removal of methylene blue using a novel magnetic chitosan-carboxymethyl cellulose/multiwalled carbon nanotubes and to identify the most significant parameters influencing the adsorption efficiency. …”
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Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model by Mahir Mohammed Sharif Adam, Nojood O. Aljehane, Mohammed Yahya Alzahrani, Samah Al Zanin

“…In this paper, an enhanced assistive Technology for Blind People through Object Detection Using a Hiking optimization algorithm (EATBP-ODHOA) technique is proposed. …”
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A metaheuristic-based approach for optimizing the allocation of emergency water reservoirs for fire following earthquake suppression by Ali Tanoumand, Mohammadreza Mashayekhi, Ali Majdi, Ehsan Noroozinejad Farsangi

“…Using a metaheuristic algorithm, the optimal allocation zones are identified based on the total distance from urban areas and the FFE risk factor. …”
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Optimal energy management of distributed generation resources in a microgrid under various load and solar irradiance conditions using the artificial bee colony algorithm by Tareq Hamadneh, Omar Alsayyed, Belal Batiha, El Manaa Barhoumi, Mehrdad Ahmadi Kamarposhti, Hassan Haghighi, Phatiphat Thounthong, Ilhami Colak

“…Abstract Optimal energy management of distributed generation and storage systems in microgrids plays a critical role in minimizing operational costs, reducing environmental emissions, improving power quality, and enhancing system reliability. …”
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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…This paper proposes a cooperative sleep and energy-sharing strategy for heterogeneous 5G base station microgrid (BSMG) systems, utilizing deep learning and an improved multi-objective evolutionary algorithm based on decomposition (MOEA/D). …”
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A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

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Opposition-based learning techniques in metaheuristics: classification, comparison, and convergence analysis by Rihab Lakbichi, Farouq Zitouni, Saad Harous, Aridj Ferhat, Abdelhadi Limane, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…In recent years, opposition-based learning (OBL) has emerged as a powerful enhancement strategy in metaheuristic algorithms (MAs), gaining significant attention for its potential to accelerate convergence and improve solution quality. …”
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Research on highway road condition intelligent assessment and optimization system based on deep learning and internet of things by Tingquan He, Changhai Wang, Riyan Lan, Haiyu Luo

“…Customizing prior information, enhancing Mixup data, improving LabelSmoothing to enhance generalization ability, and optimizing GIoU position loss and FocalLoss confidence loss are combined with the CBAM(Cost Benefit Analysis Method) module to improve network structure. …”
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Simulation study on the urban-rural integration circulatory mechanism system in China: Based on system dynamics model and multi-objective genetic algorithm by Gaoyang Liang, Mingqiang Xing, Jianqiang Zhao

“…The results indicate that all three driving forces significantly enhance the overall level of urban-rural integration, with the most substantial improvements observed in economic and social integration. …”
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Dynamic reconfiguration of the distribution systems with Load Duration Curve (LDC) model for reducing the losses and improving the voltage profile by Sana Sadeghi, Alireza Jahangiri, Ahmad Ghaderi Shamim

“…Simulations were conducted on the well-established IEEE 33-bus test system, employing MATLAB software in conjunction with a genetic algorithm to minimize losses and optimize voltage profiles. …”
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Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
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OPTIMIZATION OF FUZZY INVENTORY MANAGEMENT IN INDUSTRIAL PROCESSES USING DEEP LEARNING ALGORITHMS: A HYBRID APPROACH FOR ENHANCING DEMAND FORECASTING AND SUPPLY CHAIN EFFICIENCY by K. Kalaiarasi*, S. Swathi

“…A mathematical model and algorithmic implementation demonstrate the approach’s effectiveness and a numerical example highlights improvements in inventory control, including reduced holding costs. …”
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Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems by Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari

“…MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. …”
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Integrating GIS, 3D-Isovist, and an NSGA-II multi-objective optimization algorithm for automation of design process in urban parks and public open spaces by Karim Zandniapour, Akram Soroush, Ehsan Khezerlu Agdam, Haniyeh Sanaieian

“…The results showed that the NSGA-II was able to solve the complex design problem with 185 trees and 66 observers. The algorithm produced a Pareto-frontier consisting of four optimal solutions that, compared to the existing state of the park, showed more than 18% and 12 % improvement according to Tree View and Building View, respectively. …”
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Online Vulnerability Assessment in Cascading Failure Analysis Using an Intelligence Monitoring Model by Saber Armaghani, Zahra Moravej

“…Thus, in this paper, Demand Response modeling will be based on determining the cost of electric energy consumption in the emergency of the network in such a way as to cause a shift of consumption to improve the performance of the network. …”
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Low-carbon optimization planning method for integrated energy system based on DG uncertainty affine model by JIANG Tao, XU Cong, JIA Shaohui, WANG Shen, ZHANG Yajian

“…Then, based on the differential evolution-particle swarm optimization algorithm, the established low-carbon planning model of the integrated energy system was solved to avoid the algorithm from falling into local optimality during the optimization process. …”
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