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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A Modified Horse Herd Optimization Algorithm and Its Application in the Program Source Code Clustering by Bahman Arasteh, Peri Gunes, Asgarali Bouyer, Farhad Soleimanian Gharehchopogh, Hamed Alipour Banaei, Reza Ghanbarzadeh

“…This paper applied the horse herd optimization algorithm, a distinctive population-based and discrete metaheuristic technique, in clustering software modules. …”
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Unmanned Aerial Vehicle Path Planning Based on Sparrow-Enhanced African Vulture Optimization Algorithm by Weixiang Zhu, Xinghong Kuang, Haobo Jiang

“…In this paper, a three-dimensional model is built under a variety of constraints, and SAVOA (Sparrow-Enhanced African Vulture Optimization Algorithm) is compared with a variety of popular algorithms in simulation experiments. …”
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Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

“…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
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Tabu Genetic Cat Swarm Algorithm Analysis of Optimization Arrangement on Mistuned Blades Based on CUDA by Yi Cai, Junjie Gu, Honggang Pan, Hongyuan Zhang, Tianyu Zhao

“…Tabu genetic cat swarm optimization algorithm is proposed for optimization arrangement on mistuned blades. …”
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Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm-Random Forest Regression by Muhammad Shahzad Nazir, Sami ud Din, Wahab Ali Shah, Majid Ali, Ali Yousaf Kharal, Ahmad N. Abdalla, Padmanaban Sanjeevikumar

“…The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). …”
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Optimal Design for an Extruder Head Runner Based on Response Surface Method and Simulated Annealing Algorithm by Haichao Zhou, Zhen Jiang, Wenchao Li, Guolin Wang, Yongjie Tu

“…The response surface model was optimized using the simulated annealing (SA) algorithm, and the optimal key factors of the head runner were obtained. …”
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Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

“…Findings: The optimized LightGBM model showed significant improvement in early CHD detection. …”
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Techno-Economic Enhancement of Distribution Network by Optimal DG Allocation Along with Network Reconfiguration Considering Different Load Models and Levels by Chintan D. Patel, Tarun Kumar Tailor, Samyak S. Shah, Gulshan Sharma, Pitshou N. Bokoro

“…Therefore, this work focuses on improving DN performance with optimal DG integration along with NR. …”
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BSO-CNN: A BSO Pressure Optimized CNN Model for Water Distribution Networks by Waghmare Shwetambari Pandurang, Renu Praveen Pathak, Imtiyaz Ahmad Wani

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Metaheuristic Algorithms for Optimization and Feature Selection in Cloud Data Classification Using Convolutional Neural Network by Nandita Goyal, Munesh Chandra Trivedi

“…A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.…”
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Advanced Sales Route Optimization Through Enhanced Genetic Algorithms and Real-Time Navigation Systems by Wilmer Clemente Cunuhay Cuchipe, Johnny Bajaña Zajia, Byron Oviedo, Cristian Zambrano-Vega

“…This study proposes a novel Hybrid Genetic Algorithm (GAAM-TS) that integrates Adaptive Mutation, Tabu Search, and an LSTM-based travel time prediction model to enable real-time, intelligent route planning. …”
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Enhancing Solid Oxide Fuel Cell Efficiency Through Advanced Model Identification Using Differential Evolutionary Mutation Fennec Fox Algorithm by Manish Kumar Singla, Jyoti Gupta, Ramesh Kumar, Pradeep Jangir, Mohamed Louzazni, Nimay Chandra Giri, Ahmed Jamal Abdullah Al-Gburi, E. I.-Sayed M. EI-Kenawy, Amal H. Alharbi

“…This research introduces a novel approach for optimal SOFC model identification using a differential evolutionary mutation Fennec fox algorithm (DEMFFA). …”
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A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning by Bei Liu, Yuefeng Cai, Duantengchuan Li, Ke Lin, Guanghui Xu

“…An effective path planning algorithm can greatly improve the operational efficiency of UAVs in complex environments like urban and mountainous areas, thus offering more extensive coverage for various tasks. …”
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Robust multi-objective optimization for water flooding under geological uncertainty by Abobakr Sori, Mohammad Sharifi, Nooshin Jabari

“…By employing a multi-objective optimization (MOO) algorithm, we aim to minimize the sensitivity of objective functions to geological variability. …”
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Deep Learning-Augmented Evolutionary Strategies for Intelligent Global Optimization by Absalom El-Shamir Ezugwu, Olaide Nathaniel Oyelade, Jeffrey Ovre Agushaka, Apu Kumar Saha

“…Friedman’s test ranked SIRO 4th overall, with SSA as the top-performing algorithm. Additionally, SIRO was tested on real-world optimization problems, including mechanical engineering design, hyperparameter tuning, and feature selection for medical image classification. …”
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Stochastic sizing and energy management of a hybrid energy system using cloud model and improved Walrus optimizer for China regions by Wenjun Liao, Qing Xiong, Zilong Chen, Jinhui Tan, Pingfei Li, Hadi Gharoei

“…An improved Walrus Optimizer (IWO) with a piecewise linear chaotic map is applied to determine the optimal system component sizes. …”
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Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
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Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
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