Coordinated Operation of the Constituent Components of a Community Energy System to Maximize Benefits While considering the Network Constraints by A. H. Wijethunge, J. V. Wijayakulasooriya, J. B. Ekanayake, A. Polpitiya

“…The simulations show that the use of dynamic line rating and optimum appliance schedule provide higher profit to the community. The algorithm managed to run the optimization with 12,500 controllable entities within an average execution time of 2000s.…”
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Multi-Objective Optimization Research Based on NSGA-II and Experimental Study of Triplex-Tube Phase Change Thermal Energy Storage System by Yi Zhang, Haoran Yu, Yingzhen Hou, Neng Zhu

“…A multi-objective optimization method based on the elitist non-dominated sorting genetic algorithm (NSGA-II) was utilized to optimize the geometric dimensions (inner tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>1</mn></msub></semantics></math></inline-formula>, casing tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>2</mn></msub></semantics></math></inline-formula>, and outer tube radius <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>r</mi><mn>3</mn></msub></semantics></math></inline-formula>), focusing on heat transfer efficiency (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ε</mi></semantics></math></inline-formula>), heat storage rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>P</mi><mi>t</mi></msub></semantics></math></inline-formula>), and mass (<i>M</i>). …”
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Machine learning-driven development of a stratified CES-D screening system: optimizing depression assessment through adaptive item selection by Ruo-Fei Xu, Zhen-Jing Liu, Shunan Ouyang, Qin Dong, Wen-Jing Yan, Dong-Wu Xu

“…Conclusions This study contributes to the refinement of CES-D by developing a machine learning-derived stratified screening version, offering an efficient and reliable approach that optimizes assessment burden while maintaining excellent psychometric properties. …”
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Enhancing Adaptive Spectrum Access: An Intelligent Reflecting Surface Assisted CRN for Future Wireless Communication by Vishwas Srivastava, Binod Prasad

“…To address this, we propose an intelligent reflecting surface (IRS)-assisted enhanced ASAM (EASAM) CR network (CRN). Additionally, we optimize the IRS phase shifts and ST&#x2019;s transmit power using the Grey Wolf Optimization (GWO) algorithm. …”
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Optimizing Security of Radio Frequency Identification Systems in Assistive Devices: A Novel Unidirectional Systolic Design for Dickson-Based Field Multiplier by Atef Ibrahim, Fayez Gebali

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Artificial neural networks-based multi-objective optimization of immersion cooling battery thermal management system using Hammersley sampling method by Muhammed Donmez, Mehmet Ihsan Karamangil

“…Using the Hammersley method, various module designs are generated. Multi-objective optimization, using ANN-based multi objective genetic algorithms, is conducted on a 16S1P configuration at 4C discharge and 0.008 kg/s. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Cooperative Low-Carbon Trajectory Planning of Multi-Arrival Aircraft for Continuous Descent Operation by Cun Feng, Chao Wang, Hanlu Chen, Chenyang Xu, Jinpeng Wang

“…Firstly, this study analyzes the CDO phases of aircraft in the terminal area, establishes a multi-phase optimal control model for the vertical profile, and introduces a novel vertical profile optimization method for CDO based on a genetic algorithm. …”
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Hyperspectral imaging for precision nitrogen management: A comparative exploration of two methodological approaches to estimate optimal nitrogen rate in processing tomato by Vito Aurelio Cerasola, Francesco Orsini, Giuseppina Pennisi, Gaia Moretti, Stefano Bona, Francesco Mirone, Jochem Verrelst, Katja Berger, Giorgio Gianquinto

“…PLSR outperformed the other algorithms in estimating N uptake (Relative Root Mean Square Error, RRMSE=21.8 %), while SVR better estimated NNI (RRMSE=10.2 %) and direct biomass (RRMSE=19.4 %). …”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…Abstract The primary objective of this study is to evaluate the influence of critical process parameters on the hardness of AlSi10Mg alloy fabricated via the Laser Powder Bed Fusion (LPBF) technique. To optimize these parameters, a Taguchi-based signal-to-noise (S/N) ratio analysis was employed. …”
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Performance Optimization of a Formula Student Racing Car Using the IPG CarMaker, Part 1: Lap Time Convergence and Sensitivity Analysis by Dominik Takács, Ambrus Zelei

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Enhanced Anti-Lock Braking System Performance: A Comparative Study of Adaptive Terminal Sliding Mode Control Approaches by Salma Khatory, Houcine Chafouk, El Mehdi Mellouli

“…Gain tuning, essential for optimizing system performance and reducing tracking errors, is achieved using the efficient Teaching–Learning-Based Optimization (TLBO) algorithm. …”
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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…Using the MIMIC-IV dataset, we employ the Wolverine Optimization Algorithm (WoOA) to select clinically relevant features, followed by a Generative Pre-Training Graph Neural Network (GPT-GNN) that models complex patient relationships through self-supervised learning. …”
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An Enhanced Bio-inspired GWO–DE Technique for Efficient Feature Selection in the EEG-RSVP Paradigm by S. Abinayaa, S. S. Sridhar

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Sustainable closed-loop supply chain network design: heuristic hybrid approach with considering inflation and carbon emission policies by Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, Seyyed Mohammad Hadji Molana

“…This study aims to decide on operational and tactical levels to configure the Stable Closed Chain Supply Chain Network (SCLSC) to maximize Net Present Value (NPV) and seek to minimize carbon emissions while maintaining environmentally friendly policies and considering inflation.Methodology: This paper considers a solid Fuzzy Robust Optimization (FRO) approach to deal with stable, closed-loop supply chain uncertainties. …”
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Quantitative structure-activity relationship study of some angiotensin-converting enzyme inhibitor drugs in the treatment of hypertension based on Monte Carlo optimization method by Shahram Lotfi, Shahin Ahmadi, Ali Azimi

“…Results: A hybrid optimal descriptor computed from SMILES and molecular hydrogen-suppressed graphs is employed to construct QSAR models. …”
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A Novel ANN-PSO Method for Optimizing a Small-Signal Equivalent Model of a Dual-Field-Plate GaN HEMT by Haowen Shen, Wenyong Zhou, Jinye Wang, Hangjiang Jin, Yifan Wu, Junchao Wang, Jun Liu

“…This study introduces a novel method that integrates artificial neural networks (ANNs) with the Particle Swarm Optimization (PSO) algorithm to enhance the efficiency and precision of parameter optimization for the small-signal equivalent model of dual-field-plate GaN HEMT devices. …”
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Enhancing Hybrid Flow Shop Scheduling Problem with a Hybrid Metaheuristic and Machine Learning Approach for Dynamic Parameter Tuning by Ahmed Abdulmunem Hussein

“…Specifically, we propose a hybrid algorithm by combining Ant Colony Optimization (ACO) and Iterated Local Search (ILS) to form ACOILS. …”
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E²VRP-CPP: An Energy-Efficient Approach for Multi-UAV Multi-Region Coverage Path Planning Optimization in the Enhanced Vehicle Routing Problem by Yuechao Zang, Xueqin Huang, Min Lu, Qianzhen Zhang, Xianqiang Zhu

“…We propose an approach that optimizes UAV flight speeds to minimize energy consumption, supported by an accurate energy estimation algorithm. …”
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A Method for Improving the Monitoring Quality and Network Lifetime of Hybrid Self-Powered Wireless Sensor Networks by Peng Wang, Yonghua Xiong

“…Finally, a method based on an improved nutcracker optimizer algorithm is proposed to solve the optimal working sequence of nodes, schedule the “sleep or work” state of nodes, and extend the network lifetime. …”
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