Optimization of Hydronic Heating System in a Commercial Building: Application of Predictive Control with Limited Data by Rana Loubani, Didier Defer, Ola Alhaj-Hasan, Julien Chamoin

“…Incorporating weather forecasts, occupancy scenarios, and comfort requirements, a genetic algorithm identifies optimal hourly setpoints. This work demonstrates the possibility of creating sufficiently accurate models for this type of application using limited data. …”
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A fuzzy-optimized hybrid ensemble model for yield prediction in maize-soybean intercropping system by Amna Ikram, Sunnia Ikram, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Adil Hussain, Amal H. Alharbi, Marwa M. Eid, Marwa M. Eid

“…The FOHEM framework integrates the outputs of the FIS with a stacked ensemble model comprising Random Forest (RF), Categorical Boosting (CatBoost), and Extreme Learning Machine (ELM)). A genetic algorithm (GA) dynamically adjusts the weights between FIS and the ensemble model, optimizing final prediction while enhancing accuracy and robustness. …”
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Optimization of Ecosystem Service Bundles from a Trade-Off and Synergistic Perspective: A Case Study of Qinghai Province by Qiwei Wu, Jian Gong, Shishi Wu, Jiasheng Lin

“…Based on these synergies, we developed a novel optimization algorithm to generate spatial bundles that amplify synergistic interactions while minimizing costs. …”
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DyEHS: An Integrated Dynamo–EPANET–Harmony Search Framework for the Optimal Design of Water Distribution Networks by Francesco De Paola, Giuseppe Speranza, Giuseppe Ascione, Nunzio Marrone

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A hybrid scheduling approach for mega event transportation: integrating harmony search and black widow optimization by Mohd Khaled Shambour, Esam Khan, Muhannad A. Abu-Hashem

“…This study introduces a novel hybrid optimization algorithm that combines the strengths of harmony search (HS) and black widow optimization (BWO). …”
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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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Optimization of Multi-Energy Grid Integration and Energy Storage in Low-Carbon Power Systems Based on the TCM-MBZOA Algorithm: A Case Study of Yunnan Province by Yang Li, Guoen Zhou, Jiaqi Xue, Junwei Yang, Shi Yin

“…To address this limitation, this paper proposes a multi-source coordinated optimization strategy based on a bi-level programming model and an improved tent chaotic mapping-memory backtracking zebra optimization algorithm (TCM-MBZOA). …”
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Optimizing the eco-friendly dyeing of wool and nylon fabrics with Prangos ferulacea (L.) Lindl using artificial intelligence by Shiva Shokrzadeh, Milad Razbin, Fatemeh Shahmoradi Ghaheh, Majid Tehrani, Mehdi Sadrjahani

“…Sensitivity analysis identified pH as the most influential factor for wool (50% contribution) and dyeing duration for nylon (46% contribution). A genetic algorithm optimized the dyeing conditions, yielding ideal parameters for wool (80.8 wt.% dye concentration, 110.3 min, pH 6.1, and 80.6 °C) and nylon (68.6 wt.% dye concentration, 102.5 min, pH 5.0, and 95.0 °C). …”
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Boosting EMG classification: a hybrid NCA-driven evolutionary optimization approach for high accuracy and efficiency by X. Little Flower, S. Poonguzhali

“…Abstract A novel hybrid approach combining neighborhood component analysis (NCA) and metaheuristic optimization algorithms is proposed to improve the classification accuracy of electromyography (EMG) signals while reducing the feature set size and computational time. …”
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A Multi-Objective Optimization Study on a Certain Lecture Hall Based on Thermal and Visual Comfort by Hui Xi, Shichao Guo, Wanjun Hou, Bo Wang

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Ant Colony Optimization for Multiple Pickup and Multiple Delivery Vehicle Routing Problem with Time Window and Heterogeneous Fleets by Phan Nguyen Ky Phuc, Nguyen Le Phuong Thao

“…In the next step, the ant colony optimization algorithm is studied to solve the problem in the large-scale.…”
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Assessing the quality of whole slide images in cytology from nuclei features by Paul Barthe, Romain Brixtel, Yann Caillot, Benoît Lemoine, Arnaud Renouf, Vianney Thurotte, Ouarda Beniken, Sébastien Bougleux, Olivier Lézoray

“…To address these challenges, this article introduces a straightforward, interpretable, and computationally efficient quality control module to ensure optimal algorithmic performance. Methods: The proposed quality control module ensures algorithmic performance by representing an algorithm by a reference whole slide image preparation protocol validated on it. …”
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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

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Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…Finally, an improved genetic algorithm is employed to solve the model and determine the optimal scheduling and maintenance strategy. …”
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Comparative Evaluation of Traditional and Advanced Algorithms for Photovoltaic Systems in Partial Shading Conditions by Robert Sørensen, Lucian Mihet-Popa

“…This study focuses on the development and comparison of traditional and advanced algorithms, including Perturb and Observe (P&O), Incremental Conductance (IC), Fuzzy Logic Control (FLC), Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and Artificial Neural Networks (ANN), for efficient Maximum Power Point Tracking (MPPT). …”
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Estimating the transpiration of kiwifruit using an optimized canopy resistance model based on the synthesis of sunlit and shaded leaves by Zongyang Li, Lu Zhao, Zhengxin Zhao, Huanjie Cai, Liwen Xing, Ningbo Cui

“…This study established a rc estimation model based on a synthesis of sunlit and shaded leaves (SSL) and optimized it using Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
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Optimization of Operation Strategy of Multi-Islanding Microgrid Based on Double-Layer Objective by Zheng Shi, Lu Yan, Yingying Hu, Yao Wang, Wenping Qin, Yan Liang, Haibo Zhao, Yongming Jing, Jiaojiao Deng, Zhi Zhang

“…In this paper, the cooperative operation process of shared energy storage participating in multiple island microgrid systems is researched, and the two-stage research on multi-microgrid operation mode and shared energy storage optimization service cost is focused on. In the first stage, the output of each subject is determined with the goal of profit optimization and optimal energy storage capacity, and the modified grey wolf algorithm is used to solve the problem. …”
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A Novel, Self-Adaptive, Multiclass Priority Algorithm with VM Clustering for Efficient Cloud Resource Allocation by Hicham Ben Alla, Said Ben Alla, Abdellah Ezzati, Abdellah Touhafi

“…This algorithm implements a four-tiered prioritization system to optimize key objectives, including makespan and energy consumption, while simultaneously optimizing resource utilization, degree of imbalance, and waiting time. …”
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FHQ-RRT*: An Improved Path Planning Algorithm for Mobile Robots to Acquire High-Quality Paths Faster by Xingxiang Dong, Yujun Wang, Can Fang, Kemeng Ran, Guohui Liu

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Exploring dynamical whole-brain models in high-dimensional parameter spaces. by Kevin J Wischnewski, Florian Jarre, Simon B Eickhoff, Oleksandr V Popovych

“…To enable the parameter optimizations for the high-dimensional model fitting to empirical data, we applied two dedicated mathematical optimization algorithms (Bayesian Optimization, Covariance Matrix Adaptation Evolution Strategy). …”
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