An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…GMSMFO enhances population diversity and avoids local optima through Gaussian mutation (GM), while the shrink mechanism (SM) improves exploration–exploitation balance. Validated on the congress on evolutionary computation (CEC2020) benchmark suite (dimensions 30 and 50), GMSMFO demonstrated superior performance compared to other optimization algorithms. …”
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Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control by Yeon-Jeong Park, Joon-Ho Cho

“…The method is improved through a combination of numerical calculation, Genetic Algorithms, and LSTM networks, showing approximately 15% better performance compared to conventional methods. …”
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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Existing AutoCIL methods focus solely on single-objective optimization. However, real-world applications often involve multiple, conflicting objectives—such as predictive performance and computational cost—that must be jointly optimized. …”
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Enhancing Fuzzy C-Means Clustering with a Novel Standard Deviation Weighted Distance Measure by Ahmed Husham Mohammed, Marwan Abdul Hameed Ashour

“…It was proven  through the experimental results that  the proposed distance measure Weighted Euclidean distance  had the advantage over improving the work of the HFCM algorithm through the criterion (Obj_Fun, Iteration, Min_optimization, good fit clustering and overlap) when (c = 2,3) and according to the simulation results, c = 2 was chosen to form groups for the real data, which contributed to determine the best objective function (23.93, 22.44, 18.83) at degrees of fuzzing (1.2, 2, 2.8), while according to the degree of fuzzing (m = 3.6), the objective function for Euclidean Distance (ED) was the lowest, but the criteria were (Iter. = 2, Min_optimization = 0 and )  which confirms that (WED) is the best.…”
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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…To enhance predictive performance by transforming features, an improved Owl Search Optimization (IOSO) algorithm is used. …”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

“…To test the new FS technique and decide on an optimal set of features based on the accuracy achieved and the feature taking filters, the most recent FS approach relies on the NF-ToN-IoT dataset. …”
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Vision-Guided Maritime UAV Rescue System with Optimized GPS Path Planning and Dual-Target Tracking by Suli Wang, Yang Zhao, Chang Zhou, Xiaodong Ma, Zijun Jiao, Zesheng Zhou, Xiaolu Liu, Tianhai Peng, Changxing Shao

“…Robust target recognition is achieved using a darknet-ROS implementation of the YOLOv4 model, enhanced with data augmentation to improve performance in complex maritime conditions. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…In addition, we developed a novel hybrid feature selection model that combined correlation filtering with mutual information, Cross-Validation (CV) along with Recursive Feature Eliminatio (RFE) (R, and stability selection to identify the most impactful features. Moreover, This study develops the proposed EffiXNet, a more refined version of EfficientNet augmented with self-attention mechanisms, dynamic convolutions, improved normalization methods, and Sparrow Search Optimization Algorithm for hyperparameter optimization. …”
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Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations by Minh Thien Vo, Thi Lan Anh Tran, Quang Ai Nguyen, Trung Khanh Tran, Ngoc Dieu Vo

“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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Optimal location and size of electric vehicle charging and discharging stations in distribution networks with integrated distributed generations by Minh Thien Vo, Thi Lan Anh Tran, Quang Ai Nguyen, Trung Khanh Tran, Ngoc Dieu Vo

“…In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. …”
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Superior terahertz radiation detection through novel micro circular log-periodic antenna engineered with an advanced evolutionary neural network algorithm by Rui Zhou, Jiaqi Wang, Zhemiao Xie, Yonghai Sun, Guanxuan Lu, John T. W. Yeow

“…Abstract In this work, we introduce a novel Micro Circular Log-Periodic Antenna (MCLPA) optimized with an advanced Evolutionary Neural Network (ENN) algorithm, specifically designed to enhance terahertz (THz) radiation detection. …”
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Three-Dimensional Aerodynamic Optimization of Single-Layer Reticulated Cylindrical Roofs Subjected to Mean Wind Loads by Bingbing San, Chen Xu, Ye Qiu

“…This paper presents a procedure to optimize the rise-to-span ratio of single-layer reticulated cylindrical roofs to improve their aerodynamic performance, by coupling the optimization method with computational fluid dynamics (CFD) and finite element analysis (FEA). …”
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A Concise Review of Home Health Care Routing and Scheduling Problem by Soumen Atta, Vítor Basto-Fernandes, Michael Emmerich

“…The study examines various optimization approaches, including exact algorithms, heuristics, and metaheuristic techniques. …”
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Combining non-Monotone trust rregion method with a new adaptive radius for unconstrained optimization problems by Seyed Hamzeh Mirzaei, Ali Ashrafi

“…Purpose: One of the most effective methods for solving unconstrained optimization problems is the trust region method. …”
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Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass by Yongjie Ji, Fuxiang Zhang, Wangfei Zhang, Lei Zhao, Kunpeng Xu, Jianmin Shi, Guoran Huang, Qian Jing, Lu Wang, Feifei Yang

“…Taking advantage of available X-, C-, L-, and P-band quad-polarimetric SAR images of airborne or spaceborne for the test site located at Genhe national forest scientific field station, we used a Genetic Algorithm and Support Vector Regression optimization algorithm (GA-SVR) to explore the sensitivity of polarimetric observations at various frequencies to forest AGB and effectiveness of AGB retrievals using single-frequency, dual-frequency, triple-frequency, and quad-frequency SAR observation combinations. …”
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Route Optimization of Hazardous Material Railway Transportation Based on Conditional Value-at-Risk Considering Risk Equity by Liping Liu, Shilei Sun, Shuxia Li

“…This research offers practical decision support for transport companies and regulators, helping optimize routes while ensuring cost efficiency and regulatory compliance. …”
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A Robust Gaze Estimation Approach via Exploring Relevant Electrooculogram Features and Optimal Electrodes Placements by Zheng Zeng, Linkai Tao, Hangyu Zhu, Yunfeng Zhu, Long Meng, Jiahao Fan, Chen Chen, Wei Chen

“…The MAE and RMSE can be improved to 2.80° and 3.74° ultimately, while only using 10 features extracted from 2 channels. …”
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A correlation-based binary particle swarm optimization method for feature selection in human activity recognition by Huaijun Wang, Ruomeng Ke, Junhuai Li, Yang An, Kan Wang, Lei Yu

“…In existing works, for simplification purposes, feature selection algorithms are mostly based on the assumption of feature independence. …”
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Novel Fast Super Twisting for Dynamic Performance Enhancement of Double-Fed Induction-Generator-Based Wind Turbine: Stability Proof and Steady State Analysis by Belgacem Kheira, Atig Mebarka, Abdelli Houaria, Mezouar Abdelkader

“…To overcome these shortcomings and optimize the efficiency and performance of this technique, a new method is suggested for the super-twisting algorithm (STA). …”
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Metaheuristic Optimization of Fractional Order Incremental Conductance (FO-INC) Maximum Power Point Tracking (MPPT) by Hossam Hassan Ammar, Ahmad Taher Azar, Raafat Shalaby, M. I. Mahmoud

“…This paper seeks to improve the photovoltaic (PV) system efficiency using metaheuristic, optimized fractional order incremental conductance (FO-INC) control. …”
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