A hybrid framework: singular value decomposition and kernel ridge regression optimized using mathematical-based fine-tuning for enhancing river water level forecasting by Iman Ahmadianfar, Aitazaz Ahsan Farooque, Mumtaz Ali, Mehdi Jamei, Mozhdeh Jamei, Zaher Mundher Yaseen

“…Hence, a novel hybrid model is provided, incorporating singular value decomposition (SVD) in conjunction with kernel-based ridge regression (SKRidge), multivariate variational mode decomposition (MVMD), and the light gradient boosting machine (LGBM) as a feature selection method, along with the Runge–Kutta optimization (RUN) algorithm for parameter optimization. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…[Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Aerodynamic Optimization of Morphing Airfoil by PCA and Optimization-Guided Data Augmentation by Ao Guo, Jing Wang, Miao Zhang, Han Wang

“…A Multi-Island Genetic Algorithm (MIGA) efficiently explores the reduced design space, while iterative retraining of the surrogate model enhances prediction accuracy, particularly in high-performance regions. …”
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A Whole-Body Coordinated Motion Control Method for Highly Redundant Degrees of Freedom Mobile Humanoid Robots by Hao Niu, Xin Zhao, Hongzhe Jin, Xiuli Zhang

“…To address the high redundancy issue arising from the wheeled chassis and dual-arm design of mobile humanoid robots, this study proposes a whole-body coordinated motion control algorithm based on arm potential energy optimization. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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Efficient Frequency Management for Hybrid AC/DC Power Systems Based on an Optimized Fuzzy Cascaded PI−PD Controller by Awadh Ba Wazir, Sultan Alghamdi, Abdulraheem Alobaidi, Abdullah Ali Alhussainy, Ahmad H. Milyani

“…The SBOA-FCPIPD controller’s ITAE value is 0.5101, while sine cosine adopted an improved equilibrium optimization algorithm-based adaptive type 2 fuzzy PID controller and obtained 4.3142. …”
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Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Its objective is to identify the most optimal features in a dataset by eliminating redundant data while preserving the highest possible classification accuracy. …”
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Peak-to-average power ratio reduction of orthogonal frequency division multiplexing signals using improved salp swarm optimization-based partial transmit sequence model by Vandana Tripathi, Prabhat Patel, Prashant Kumar Jain, Shailja Shukla

“…Therefore, an optimization algorithm, namely, the improved salp swarm optimization algorithm (ISSA), is incorpo-rated with the PTS to reduce the PAPR of the OFDM signals with limited com-putational cost. …”
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A novel Probabilistic Bi-Level Teaching–Learning-Based Optimization (P-BTLBO) algorithm for hybrid feature extraction and multi-class brain tumor classification using ResNet-50 and... by Mahananda Malkauthekar, Avinash Gulve, Ratnadeep Deshmukh

“…Experimental findings indicate that the P-BTLBO algorithm surpasses conventional optimization methods, including TLBO and PSO, regarding classification accuracy, feature subset size, and computational efficiency. …”
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An improved catastrophe progression method based on HMSLGWO–AHP for grouting quality assessment by Yushan Zhu, Zhu Yang, Ning Li, Jian Huang

“…Subsequently, the analytic hierarchy process (AHP) method improved by the hierarchical multi‐strategy learning gray wolf optimization (HMSLGWO) algorithm is employed to determine the relative significance of indices, in which, the HMSLGWO algorithm, augmented by Gaussian mixture model clustering and multi‐strategy learning, optimizes the consistency of the AHP judgment matrix. …”
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Bacterial Colony Optimization by Ben Niu, Hong Wang

“…This paper investigates the behaviors at different developmental stages in Escherichia coli (E. coli) lifecycle and developing a new biologically inspired optimization algorithm named bacterial colony optimization (BCO). …”
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Smart Energy Strategy for AC Microgrids to Enhance Economic Performance in Grid-Connected and Standalone Operations: A Gray Wolf Optimizer Approach by Sebastian Lobos-Cornejo, Luis Fernando Grisales-Noreña, Fabio Andrade, Oscar Danilo Montoya, Daniel Sanin-Villa

“…To assess performance, 100 independent runs per method were conducted, comparing GWO against particle swarm optimization (PSO) and genetic algorithms (GAs). Statistical analysis confirmed that GWO achieved the lowest operational costs (USD 3299.39 in grid-connected mode and USD 11,367.76 in islanded mode), the highest solution stability (0.19% standard deviation), and superior voltage regulation. …”
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Optimizing deep belief network for concrete crack detection via a modified design of ideal gas molecular dynamics by Tan Qin, Gongxing Yan, Huaguo Jiang, Minqi Shen, Andrea Settanni

“…The present research concentrates on the development of crack diagnosis algorithms based on vision using an optimized version of Deep Neural Network (DNN). …”
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Enhancing agricultural sustainability: Optimizing crop planting structures and spatial layouts within the water-land-energy-economy-environment-food nexus by Haowei Wu, Zhihui Li, Xiangzheng Deng, Zhe Zhao

“…In this framework, the NSGA-II algorithm was used to construct the multi-objective optimization model of crop planting structures with consideration of water and energy consumption, greenhouse gas (GHG) emissions, economic benefits, as well as food, land, and water security constraints, while the model for planting spatial layout optimization was established with consideration of crop suitability using the MaxEnt model and the improved Hungarian algorithm. …”
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AI driven automation for enhancing sustainability efforts in CDP report analysis by Ramya Rangarajan, Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Venyaa Venkataraman, Krithik Shankar

“…Abstract The need for sustainable practices in supply chains is becoming increasingly critical, as businesses face pressure to reduce their carbon footprint while maintaining operational efficiency. This paper proposes a novel hybrid approach that combines Genetic Algorithms (GA) with Long Short-Term Memory (LSTM) networks to optimize supply chain sustainability. …”
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A GAN-Based Method for Cognitive Covert Communication UAV Jamming-Assistance Under Fully Labeled Sample Conditions by Wenxuan Fu, Bo Li, Haipeng Wang, Haochen Gong, Xiang Lin

“…The numerical results show that, compared with the commonly used multi-objective optimization algorithm or nonlinear programming algorithm at present, this algorithm exhibits faster and more stable convergence, enabling the derivation of optimal mobile interference assistance schemes for cognitive CC systems.…”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

“…A novel hybrid framework was put forth for consideration, comprising three distinct stages: Clustering, Parallel Filtering, and Hybrid-Parallel Optimization. In each step, a combination of techniques and algorithms is used to improve the results in terms of stability and/or accuracy. …”
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An AI-ISM Methodology for Structural Modeling of Sustainable Supply Chain Management Drivers by Reza Roshanpour, Mohammadreza Parsanejad, Mir Saman Pishvaee

“…To address these challenges, this study proposes a novel Hybrid AI-ISM methodology, integrating Genetic Algorithms (GA) to optimize the reachability matrix by minimizing transitivity violations and reciprocal inconsistencies. …”
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Advanced methodology for maximum torque point tracking of hybrid excitation PMSM for EVs by Mahmoud M. Elymany, Nadia A. Elsonbaty, Aymen FLah, Lukas Prokop, Habib Kraiem, Mohamed A. Enany, Ahmed A. Shaier

“…Additionally, the Multi-Objective Ant Lion Optimizer (MOALO) algorithm is used in two stages: first to optimize the hybridization ratio (HR) and base speed (N b ), and second to analyze the effect of varying the hybridization ratio while maintaining constrained output power. …”
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Design of a Lorentz Force Magnetic Bearing Group Steering Law Based on an Adaptive Weighted Pseudo-Inverse Law by Chenyu Wang, Lei Li, Weijie Wang, Yanbin Zhao, Baiqi Li, Yuan Ren

“…Incorporating spacecraft maneuvering requirements, a genetic optimization algorithm establishes the optimal mounting configuration under task constraints. …”
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