Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm by Hadeer Khalifa, Mohamed Ebeed, Gaber Magdy, Sherif A. Khaleel, Mohamed I. Shehata, Moataz M. Salah, Francisco Jurado, Hossam Hassan Ali

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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…This paper introduces a novel hyperparameter optimization framework for regression tasks called the Combined-Sampling Algorithm to Search the Optimized Hyperparameters (CASOH). …”
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Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

“…A new classification model of electrocardiogram (ECG) signal based on particle swarm optimization feature selection (PSOFS) and TSK (Takagi-Sugeno-Kang) fuzzy system was proposed, i.e., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
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Optimizing Vehicle Routing for Perishable Products with Time Window Constraints: by Rifqi Fauzi, Adi Priansyah, Paskalis Krisna Puspadewa, Syifa Maulvi Zainun Awal, Huu Tho Nguyen, Achmad Pratama Rifai

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Improving the area-preserving parameterization of rational Bézier surfaces by rational bilinear transformation by Xiaowei Li, Yingjie Wu, Yaohui Sun, Xin Chen, Yanru Chen, Yi-jun Yang

“…To improve the area-preserving parameterization quality of rational Bézier surfaces, an optimization algorithm using bilinear reparameterization is proposed. …”
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Analysis of Unmanned Surface Vehicles Heading KF-Based PI-(1+PI) Controller Using Improved Spider Wasp Optimizer by Xiaoyu Li, Xiangye Zeng, Jingyi Wang, Qi Li, Baoshuo Fan, Qi Zeng

“…This paper proposes a Kalman filter-based cascaded PI-(1+PI) controller, optimized using an Improved Spider Wasp Optimizer (ISWO), to address the challenges of USV heading control in dynamic marine environments. …”
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Puma algorithm for environmental emissions and generation costs minimization dispatch in power systems by Badr Al Faiya, Ghareeb Moustafa, Hashim Alnami, Ahmed R. Ginidi, Abdullah M. Shaheen

“…It efficiently navigates the solution space by balancing exploration and exploitation, leveraging puma-like intelligence to minimize both fuel costs and greenhouse gas emissions, including CO2, NOx, and SO2. The POO algorithm is tested on the IEEE 30-bus power system with six thermal units, delivering superior performance compared to advanced optimization algorithms such as the Osprey Optimization Algorithm (OOA), Aquila Optimizer (AO), Slim Mould Algorithm (SMA), Artificial Rabbit Optimization (ARO), and Coati optimization technique. …”
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Dam Deformation Data Preprocessing with Optimized Variational Mode Decomposition and Kernel Density Estimation by Siyu Chen, Chaoning Lin, Yanchang Gu, Jinbao Sheng, Mohammad Amin Hariri-Ardebili

“…The approach systematically processes data in three steps: First, VMD decomposes raw data into intrinsic mode functions without recursion. The parallel Jaya algorithm is used to adaptively optimize VMD parameters for improved decomposition. …”
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Optimal rule-based energy management and sizing of a grid-connected renewable energy microgrid with hybrid storage using Levy Flight Algorithm by Babangida Modu, Md Pauzi Abdullah, Abdulrahman Alkassem, Mukhtar Fatihu Hamza

“…The research problem focuses on improving the effectiveness and computational efficiency of energy management systems (EMS) while ensuring high system reliability. …”
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Mathematical Formulation of Intelligent Management Algorithms for Isolated Microgrids: A Pareto-Based Critical Approach by Vitor dos Santos Batista, Thiago Mota Soares, Maria Emília de Lima Tostes, Ubiratan Holanda Bezerra, Hugo Gonçalves Lott

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Dynamic multi-criteria scheduling algorithm for smart home tasks in fog-cloud IoT systems by Ruchika Bhakhar, Rajender Singh Chhillar

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A Tuning Method for Speed Tracking Controller Parameters of Autonomous Vehicles by Jianqiao Chen, Guofu Tian

“…Traditional PID controllers often struggle with maintaining accuracy and response time in highly variable conditions, but by optimizing these parameters through the genetic algorithm, substantial improvements in speed control precision and adaptability can be achieved, enhancing the vehicle’s ability to navigate real-world driving scenarios with greater stability. …”
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The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…Experimental results demonstrate that machine learning models effectively capture cultural preferences, and HBA significantly enhances marketing effectiveness, leading to a 20% increase in engagement and a 15% improvement in click-through rates (CTR). Natural Language Processing (NLP) methods are used to gain cultural insights from consumer data, while clustering algorithms segment the market based on these factors. …”
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Optimizing Class Imbalance in Facial Expression Recognition Using Dynamic Intra-Class Clustering by Qingdu Li, Keting Fu, Jian Liu, Yishan Li, Qinze Ren, Kang Xu, Junxiu Fu, Na Liu, Ye Yuan

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Optimization of delivery routes for takeout under time-varying road networks by Jiaci Wang, Liang Huang, Yuanqiao Wen, Yamin Huang, Man Zhu

“…The proposed model is solved using a taboo search algorithm. The effectiveness of the delivery model and algorithm is validated through simulations that compare the performance of the delivery route model under different weather conditions and road obstacle coefficients. …”
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A Novel, Self-Adaptive, Multiclass Priority Algorithm with VM Clustering for Efficient Cloud Resource Allocation by Hicham Ben Alla, Said Ben Alla, Abdellah Ezzati, Abdellah Touhafi

“…This algorithm implements a four-tiered prioritization system to optimize key objectives, including makespan and energy consumption, while simultaneously optimizing resource utilization, degree of imbalance, and waiting time. …”
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An Optimized Hybrid Model for Perishable Product Quality Inference in the Food Supply Chain by Muhammad Asrol, . Suharjito, Riyanto Jayadi

“…This research contributes to improving the model by employing genetic algorithms in optimizing the inference model by activating only five out of seven rules. …”
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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

“…To address this, we propose Smoothed Partial Swarm Optimization with Improved Potential Field (SPSO-IPF), combining both approaches and it is capable of generating a smooth and safe path. …”
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Enhanced Crop Leaf Area Index Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach by Jun Zhang, Jinpeng Cheng, Cuiping Liu, Qiang Wu, Shuping Xiong, Hao Yang, Shenglong Chang, Yuanyuan Fu, Mohan Yang, Shiyu Zhang, Guijun Yang, Xinming Ma

“…The Leaf Area Index (LAI) is a crucial structural parameter linked to the photosynthetic capacity and biomass of crops. While integrating machine learning algorithms with spectral variables has improved LAI estimation over large areas, excessive input parameters can lead to data redundancy and reduced generalizability across different crop species. …”
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