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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Evaluation of Environmental Factors Influencing Photovoltaic System Efficiency Under Real-World Conditions by Krzysztof Pytel, Wiktor Hudy, Roman Filipek, Malgorzata Piaskowska-Silarska, Jana Depešová, Robert Sito, Ewa Janiszewska, Izabela Sieradzka, Krzysztof Sulkowski

“…In order to advance the analysis beyond conventional methods, a linear regression model was developed in which the model weights were optimized using evolutionary algorithms, allowing for a more robust assessment of the contribution of each parameter. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…Two experimental studies validate the approach: the first systematically evaluates multiple predefined shading patterns to identify optimal characteristics, while the second demonstrates that algorithmic optimization of highly irregular shading configurations can simultaneously improve multiple visual comfort metrics, significantly outperforming regular shading patterns in terms of glare reduction, view preservation, and spatial frequency performance.…”
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Real time weed identification with enhanced mobilevit model for mobile devices by Xiaoyan Liu, Qingru Sui, Zhihui Chen

“…Abstract Deep learning model optimization have notably enhanced weed identification accuracy. …”
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Evaluation of the Geomorphon Approach for Extracting Troughs in Polygonal Patterned Ground Across Different Permafrost Environments by Amin Wen, Tonghua Wu, Xiaofan Zhu, Jie Chen, Jianzong Shi, Peiqing Lou, Dong Wang, Xin Ma, Xiaodong Wu

“…The results show that (i) the lowest <i>t</i> value (0°) captured the microtopograhy of the troughs, while the larger <i>L</i> values paired with a DEM resolution of 50 cm diminished the impact of minor noise, improving the accuracy of trough detection; (ii) the optimized Geomorphon model produced trough maps with a high accuracy, achieving mIOU and F1 Scores of 0.89 and 0.90 in PB and 0.84 and 0.87 in WDL, respectively; and (iii) compared with the polygonal boundaries, the trough maps can derive the heterogeneous features to quantify the degradation of PPG. …”
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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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A Biased–Randomized Iterated Local Search with Round-Robin for the Periodic Vehicle Routing Problem by Juan F. Gomez, Antonio R. Uguina, Javier Panadero, Angel A. Juan

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The Robust Steiner Team Orienteering Problem with Decreasing Priorities under budgeted uncertainty by Lucas Assunção, Andréa Cynthia Santos

“…The goal is to find robust feasible routes maximizing the priorities collected, while considering the worst-case conditions of service times within an uncertainty budget and a routes’ duration limit. …”
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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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Nondestructive detection and classification of impurities-containing seed cotton based on hyperspectral imaging and one-dimensional convolutional neural network by Yeqi Fei, Zhenye Li, Tingting Zhu, Zengtao Chen, Chao Ni

“…By applying hyperspectral imaging and a one-dimensional deep learning algorithm, we detect and classify impurities in seed cotton after harvest. …”
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Module Configuration of Rail Freight Transportation with Both Customer Segmentation and Product Family Genealogy in China by Weiya Chen, Shiying Tong, Ziyue Yuan, Xiaoping Fang

“…Customers have yielded eleven distinct groups, and operational processes have been segmented into sixteen modules by using the Ant Colony Optimization-based Fuzzy C-Means Clustering (ACOFCM) 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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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

“…Utilizing the deep deterministic policy gradient (DDPG) algorithm, we introduce a two-stage policy learning approach designed to optimize secrecy energy efficiency (SEE) while ensuring secure communication, even in the presence of multiple eavesdroppers (Eves). …”
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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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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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Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsu... by Sasitorn Kaewman, Raknoi Akararungruangkul

“…We developed two metaheuristics&mdash;a differential evolution (DE) algorithm and an adaptive large neighborhood search (ALNS)&mdash;to solve the problem. …”
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A Comparative Study Between Soft Actor-Critic (SAC) and Deep Deterministic Policy Gradient (DDPG) Algorithms for Solar PV MPPT Control Under Partial Shading Conditions by Sampson E. Nwachukwu, Komla A. Folly, Kehinde O. Awodele

“…However, due to the intermittent nature of PV arrays, the Maximum Power Point Tracking (MPPT) algorithm is typically employed to optimize the system&#x2019;s energy production. …”
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A web-based tool for predicting gastric ulcers in Chinese elderly adults based on machine learning algorithms and noninvasive predictors: A national cross-sectional and cohort stud... by Xingjian Xiao, Xiaohan Yi, Zumin Shi, Zongyuan Ge, Hualing Song, Hailei Zhao, Tiantian Liang, Xinming Yang, Suxian Liu, Bo Sun, Xianglong Xu

“…Objective Our study aims to employ machine learning algorithms to predict the occurrence of gastric ulcers and develop an online tool to assess the risk of gastric ulcers for elderly individuals, both currently and in the future, while identifying important predictors. …”
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LHS-GA Based H-Infinity Control for Robust Airfoil Flutter Suppression by Malek Rekik, Omar Khaled, Karolos Grigoriadis, Matthew A. Franchek

“…The objective is to design a robust controller that effectively suppresses flutter while optimizing performance metrics, specifically time-domain constraints and settling time. …”
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