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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Advanced skin cancer prediction with medical image data using MobileNetV2 deep learning and optimized techniques by Tuğçe Öznacar, Nuray Varol Kayapunar

“…These results underscore the potential of deep learning models, optimized with the memetic algorithm, to significantly improve skin cancer detection. …”
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Orthogonal Multi‐Swarm Greedy Selection Based Sine Cosine Algorithm for Optimal FACTS Placement in Uncertain Wind Integrated Scenario Based Power Systems by Sunilkumar P. Agrawal, Pradeep Jangir, Arpita, Sundaram B. Pandya, Anil Parmar, Mohammad Khishe, Bhargavi Indrajit Trivedi

“…Flexible AC Transmission System (FACTS) devices, including Static VAR Compensator (SVC), Thyristor‐Controlled Series Compensator (TCSC), and Thyristor‐Controlled Phase Shifter (TCPS), enhance system stability, reduce losses, and lower operational costs when optimally placed. Conventional optimization techniques like Particle Swarm Optimization (PSO), Sine Cosine Algorithm (SCA), Moth Flame Optimization (MFO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) struggle to balance exploration and exploitation in complex OPF problems, leading to suboptimal solutions. …”
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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…In comparison to manually designed HDLM, the proposed approach achieves up to 97.86% model compression with a 0.34% accuracy improvement, while a variant achieves 96.24% compression with a 0.23% accuracy improvement. …”
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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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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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A hybrid GA-SA resource allocation scheme enhanced with SINR optimization for NOMA-MIMO systems in 5G networks by Murad Halabouni, Mardeni Roslee, Sufian Mousa Ibrahim Mitani, Osama M.S. Abujawa, Anwar Faizd Osman, Fatimah Zaharah Ali

“…Genetic Algorithm (GA) optimizes user pairing by evolving high-throughput configurations, while Simulated Annealing (SA) refines power allocation to maximize Signal-to-Interference-plus-Noise Ratio (SINR) and minimize interference. …”
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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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A Comparative Study on DG Placement Using Marine Predator and Osprey Algorithms to Enhance Loss Reduction Index in the Distribution System by Syazwan Ahmad Sabri, Siti Rafidah Abdul Rahim, Azralmukmin Azmi, Syahrul Ashikin Azmi, Muhamad Hatta Hussain, Ismail Musirin

“…The Marine Predator Algorithm (MPA) and Osprey Optimization Algorithm (OOA) are nature-inspired metaheuristic techniques used for optimizing the location and sizing of distributed generation (DG) in power distribution systems. …”
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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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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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AI based data-driven point cloud optimization strategy in cloud computing framework for improving rendering performance of virtual city scenes by Cao Zhongda

“…To address the problem of poor rendering of virtual city scene, the paper proposes an Artificial Intelligence (AI) based bundle adjustment point cloud optimization model based on cross-entropy loss by combining with the multi-detail hierarchy technique, the rendering efficiency is improved while guaranteeing the high consistency between the 3D model and the real world in terms of geometry. …”
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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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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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A hybrid model for short-term offshore wind power prediction combining Kepler optimization algorithm with variational mode decomposition and stochastic configuration networks by Bingbing Yu, Yonggang Wang, Jun Wang, Yuanchu Ma, Wenpeng Li, Weigang Zheng

“…To enhance the stability and accuracy of wind power forecasting, a hybrid model integrating Kepler optimization algorithm (KOA), variational mode decomposition (VMD), and stochastic configuration network (SCN) is proposed. …”
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Modeling methylene blue removal using magnetic chitosan carboxymethyl cellulose multiwalled carbon nanotube composite with genetic algorithms and regression techniques by Mahmood Yousefi, Saeid Fallahizadeh, Yosra Maleki, Amir Sheikhmohammadi, Alieh Rezagholizade-shirvan

“…The result of Genetic Algorithm analysis also proved the model has converged to the optimal solution effectively, the best solution of X1 = 49.41, X2 = 110.62, X3 = 11.85 and X4 = 20 which gives the maximum removal efficiency = 94.64% of methylene blue. …”
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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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PSO-FDM (Particle Swarm Optimization-Finite Difference Method)-Based Simulation Model of Temperature and Velocity of Full-Scale Continuous Annealing Furnace by Yang Liu, Qiang Guo, Tieheng Yuan, Yingrui Han, Chao Liu, Wenquan Sun

“…This paper developed a continuous annealing temperature prediction model based on a variable step-size strategy for the heating section, even-heat section, slow-cooling section, and fast-cooling section of the continuous annealing line. To improve the prediction accuracy for different strip sizes, the PSO optimization algorithm was employed to determine the optimal heat transfer coefficient for each strip size. …”
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Power quality enhancement based disturbance rejection controller in microgrid system using walrus optimization algorithm and multi-functional recurrent fuzzy neural network by Ali M.H. Al Thaiban, Akram Elmitwally, Abdelhady Ghanem, Ahmed I. Omar

“…The UPQC’s control is executed through a Fractional Order-Active Disturbance Rejection Controller (FOADRC) that employs the Innovative Walrus Optimization Algorithm (WOA) to ascertain optimal gain values for the control method across numerous PQ scenarios, while the Multi-Functional Recurrent Fuzzy Neural Network (MFRFNN) predicts control parameters for adaptive system regulation. …”
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SOE: A Multi-Objective Traffic Scheduling Engine for DDoS Mitigation with Isolation-Aware Optimization by Mingwei Zhou, Xian Mu, Yanyan Liang

“…These objectives are combined into a composite scalarized loss function with soft constraints, prioritizing a BTAR while maintaining flexibility. To solve this problem, we introduce MOFATA, a multi-objective extension of the Fata Morgana Algorithm (FATA) within a Pareto-based evolutionary framework. …”
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