Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace Applications by João P. Castanheira, Beltran N. Arribas, Rui Melicio, Paulo Gordo, André R. R. Silva

“…This research employs a series of numerical simulations using methods such as Genetic Algorithms, Cultural Algorithms, and Artificial Immune Systems, with an emphasis on parameter tuning to optimize the reduced thermal model correlation. …”
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A Numerical Modeling Study of a New Type of Hydraulic Mechanical Continuously Variable Transmission (HMCVT) with Optimized Transmission Efficiency by Zexin Ma, Zhengyu Li, Deming Sun, Yanbin Cai, Jiwei Zhang, Hongyu Liu, Qingxin Wang, He Li, Long Zhou, Wenbin Yu, Feiyang Zhao

“…Secondly, an improved NSGA-II genetic algorithm was adopted to achieve dynamic optimization of shifting points through transmission parameter combination optimization, ensuring smooth shifting while improving overall transmission efficiency. …”
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Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction by ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao

“…[Conclusions] This study develops a multi-objective scheduling model for cascade reservoirs during the impoundment period and analyzes the nonlinear synergy and competitive relationships between carbon emissions and traditional water resource utilization benefits. The NSGA-Ⅱ optimization solutions significantly improv the long-term average power generation and storage rate while reducing greenhouse gas emissions without compromising flood control standards. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

“…Fractional‐Order Proportional‐Integral with Tilt Integral Double Derivative and Filter (FOPI‐TIDDN), a novel cascade controller optimized using the crow search (CS) algorithm, is proposed in this paper to overcome these issues. …”
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A structural health monitoring data reconstruction method based on VMD and SSA-optimized GRU model by Xiaoliang Jia, Guoyan Zhang, Zhiqiang Wang, Huacong Li, Jing Hu, Songlin Zhu, Caiwei Liu

“…To address this challenge, this study develops a method combining Variational Mode Decomposition (VMD) and Sparrow Search Algorithm (SSA)-optimized Gate Recurrent Unit (GRU) for recovering structural response data. …”
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Polar Code BP Decoding Optimization for Green 6G Satellite Communication: A Geometry Perspective by Chuanji Zhu, Yuanzhi He, Zheng Dou

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Development and Fuel Economy Optimization of Series–Parallel Hybrid Powertrain for Van-Style VW Crafter Vehicle by Ahmed Nabil Farouk Abdelbaky, Aminu Babangida, Abdullahi Bala Kunya, Péter Tamás Szemes

“…A MATLAB (R2024b) Simulink model of the hybrid system is developed, and its speed tracking PID controller is optimized using genetic algorithm (GA) and particle swarm optimization (PSO) methods. …”
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Smart Building Electrical Energy Optimization Through Neural Network Techniques by El Kamili Moad, Touairi Souad, Mabrouki Mustapha

“…A neural network-based control algorithm was developed and implemented in the building electrical systems for real-time energy optimization. …”
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Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees by Shobha Aswal, Neelu Jyothi Ahuja, Ritika Mehra

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Structural Damage Identification Using PID-Based Search Algorithm: A Control-Theory Inspired Application by Kuang Shi, Tingting Sun

“…With 1–3% noise, PSA maintains precise damage localization despite minor severity estimation errors, while other algorithms exhibit false positives in intact elements. …”
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An Environmentally Adaptive CRO-SL Algorithm Based on Dynamic Agents for the Channel Assignment Problem in Wireless Networks by Antonio J. Romero-Barrera, Luis Cruz-Piris, Marino Tejedor-Romero, Jose Manuel Gimenez-Guzman, Ivan Marsa-Maestre

“…In recent decades, metaheuristic algorithms have emerged as indispensable tools for addressing complex optimization challenges, particularly in several engineering fields, where NP-hard problems are prevalent. …”
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Multi-Project Staff Scheduling Optimization Considering Employee Welfare in Construction Projects by Junlong Peng, Fei Zhou

“…The experimental results demonstrate that SWOIM outperforms conventional optimization algorithms in convergence speed, stability, and solution quality. …”
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Optimizing high voltage gain interleaved boost converters for PV and wind systems using hybrid deep learning with bitterling fish and secretary bird algorithms by G.Veera Sankara Reddy, S. Vijayaraj

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MSCSO: A Modified Sand Cat Swarm Algorithm for 3D UAV Path Planning in Complex Environments with Multiple Threats by Zhengsheng Zhan, Dangyue Lai, Canjian Huang, Zhixiang Zhang, Yongle Deng, Jian Yang

“…To improve the global search efficiency and dynamic adaptability of the Sand Cat Swarm Optimization (SCSO) algorithm for UAV path planning in complex 3D environments, this study proposes a Modified Sand Cat Swarm Optimization (MSCSO) algorithm by integrating chaotic mapping initialization, Lévy flight–Metropolis hybrid exploration mechanisms, simulated annealing–particle swarm hybrid exploitation strategies, and elite mutation techniques. …”
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Optimal Protection Coordination for Grid-Connected and Islanded Microgrids Assisted by the Crow Search Algorithm: Application of Dual-Setting Overcurrent Relays and Fault Current L... by Hossien Shad, Hamid Amini Khanavandi, Saeed Abrisham Foroushan Asl, Ali Aranizadeh, Behrooz Vahidi, Mirpouya Mirmozaffari

“…To solve this complex optimization problem, the Crow Search Algorithm (CSA) is employed, ensuring the derivation of reliable and effective solutions. …”
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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

“…Fuzzy logic offers a robust framework for decisionmaking under uncertainty, while deep learning improves predictive accuracy by identifying complex patterns in historical data. …”
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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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Isolation Enhancement Based on TM010 and TE30 Mode Characteristics in a Patch Antennas Using Genetic Algorithm Optimization for Ku-Band Applications by Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

“…The design utilized a Rogers 3003 series dielectric substrate with a dielectric constant of 3.3 and a loss tangent of 0.003. A genetic algorithm with tournament selection and a multiobjective function was applied to optimize key performance metrics, such as impedance matching, bandwidth, and gain. …”
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Optimization of additive contents in cottonseed meals during the solid-state fermentation using response surface methodology and artificial neural network-based genetic algorithm by TANG Jiang-wu, SUN Hong, YAO Xiao-hong, WU Yi-fei, WANG Xin

“…The correlation efficiency of 0.9191 identified by response surface methodology was a little lower than that of 0.9991 identified by genetic algorithm based on an artificial neural network model, which also was with a lower RMSE value by 0.13, indicating that the artificial neural network-based genetic algorithm had a much higher optimizing ability and modeling ability during the optimization of the solid-state fermentation process.…”
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GenePixKolor (GPK) Fusion: A Novel Evolutionary Algorithm-Based Optimized NFT Card Generation and Rarity Ranking Method for Gaming Tokenomics by J. Guruprakash, P. Pradeep, L. B. Krithika

“…GPK Fusion leverages genetic algorithms, image processing and machine learning to create a comprehensive, four-stage system that optimizes both the trait generation and visual appeal of NFTs, while providing an advanced rarity ranking mechanism. …”
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