A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting by Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, Mikko Kolehmainen

“…The proposed algorithm simultaneously optimizes both hyperparameters and feature sets across six different ML models, ensuring enhanced accuracy and efficiency. …”
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A Hierarchical Path Planning Framework of Plant Protection UAV Based on the Improved D3QN Algorithm and Remote Sensing Image by Haitao Fu, Zheng Li, Jian Lu, Weijian Zhang, Yuxuan Feng, Li Zhu, He Liu, Jian Li

“…To address these challenges, this study proposes a deep reinforcement learning algorithm, MoE-D3QN, which integrates a Mixture-of-Experts mechanism with a Bi-directional Long Short-Term Memory model. …”
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Multiobjective Optimization of Turbine Coolant Collection/Distribution Plenum Based on the Surrogate Model by Junsheng Chai, Zhenyu Wang, Xuanling Zhao, Chunhua Wang

“…Based on these data sampling, least square support vector machine (LS-SVM) was used for the surrogate model, and a kind of chaotic optimization algorithms was used for searching for the Pareto solution set. …”
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Optimization design of an acoustic cover layer for a cylindrical cavity based on porous materials by Bohan ZHANG, Jili RONG, Xiuyan CHENG

“…In this study, a comprehensive investigation into the parameter fitting and acoustic performance optimization of porous materials is conducted, utilizing advanced physical models, multifluid impedance transfer theory, and particle swarm optimization algorithms. …”
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An Integrated Supply Chain Model for Predicting Demand and Supply and Optimizing Blood Distribution by Pooria Bagher Niakan, Mehdi Keramatpour, Behrouz Afshar-Nadjafi, Alireza Rashidi Komijan

“…Genetic algorithms (GA) and particle swarm optimization (PSO) are used to solve mathematical models quickly and efficiently, ensuring reliable operation. …”
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Differentiable Deep Learning Surrogate Models Applied to the Optimization of the IFMIF-DONES Facility by Galo Gallardo Romero, Guillermo Rodríguez-Llorente, Lucas Magariños Rodríguez, Rodrigo Morant Navascués, Nikita Khvatkin Petrovsky, Rubén Lorenzo Ortega, Roberto Gómez-Espinosa Martín

“…The substantial speed-up factors enable the application of online reinforcement learning algorithms, and the differentiable nature of the models allows for seamless integration with differentiable programming techniques, facilitating the solving of inverse problems to find the optimal parameters for a given objective. …”
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Application of Machine Learning Models in Optimizing Wastewater Treatment Processes: A Review by Florin-Stefan Zamfir, Madalina Carbureanu, Sanda Florentina Mihalache

“…Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. …”
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A Novel DV-Hop Localization Method Based on Hybrid Improved Weighted Hyperbolic Strategy and Proportional Integral Derivative Search Algorithm by Dejing Zhang, Pengfei Li, Benyin Hou

“…Secondly, the localization error is further reduced by employing the improved PSA. In addition, the selection process of the node set is optimized using progressive sample consensus (PROSAC) followed by a 3D hyperbolic algorithm based on coplanarity. …”
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Mexican axolotl optimization algorithm with a recalling enhanced recurrent neural network for modular multilevel inverter fed photovoltaic system by R. Madavan, B. Karthikeyan, R. Palanisamy, Mohammad Imtiyaz Gulbarga, Mohammed Al Awadh, Liew Tze Hui

“…The proposed MAO-RERNN control method integrates the Mexican Axolotl Optimization (MAO) algorithm with a Recalling-Enhanced Recurrent Neural Network (RERNN) to achieve optimal power conversion, improved stability, and reduced total harmonic distortion (THD). …”
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Logistics Hub and Route Optimization in the Physical Internet Paradigm by Hisatoshi Naganawa, Enna Hirata, Nailah Firdausiyah, Russell G. Thompson

“…<i>Methods:</i> We propose a novel demography-weighted combinatorial optimization model utilizing a genetic algorithm and the Lin–Kernighan heuristic. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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Intelligent anti-jamming decision algorithm of bivariate frequency hopping pattern based on ET-PPO by Yibo CHEN, Zhijin ZHAO

“…In order to further improve its anti-interference ability in complex electromagnetic environment, a PPO algorithm based on weighted importance sampling and eligibility traces (ET-PPO) was proposed.On the basis of the traditional frequency hopping pattern, time-varying parameters were introduced, and the bivariate frequency hopping pattern decision problem was modeled as a Markov decision problem through the construction of the state-action-reward triple.Aiming at the high variance problem of the sample update method of an actor network of the PPO algorithm, weighted importance sampling was introduced to reduce the variance, and the action selection strategy of Beta distribution was used to enhance the stability of the learning stage.Aiming at the problem of slow convergence speed of the evaluator network, the eligibility trace method was introduced, which better balanced the convergence speed and the global optimal solution.The algorithm comparison simulation results in different electromagnetic interference environments show that ET-PPO has better adaptability and stability, and has better performance against obstruction interference and sweep frequency interference.…”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…This approach improved the accuracy and robustness of structural parameter identification while maintaining computational efficiency.MethodsMOMDBA is an enhanced version of the Directional Bat Algorithm （DBA）， a swarm intelligence optimization technique inspired by the echolocation behavior of bats. …”
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Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

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E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

“…To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.…”
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Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method by Aichen Wang, Yuanzhi Xu, Dong Hu, Liyuan Zhang, Ao Li, Qingzhen Zhu, Jizhan Liu

“…The particle swarm optimization (PSO) algorithm was used to optimize the detection region, thus enhancing the counting accuracy. …”
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A New Method for Spectral Wavelength Selection Based on Multiple Linear Regression Combined with Ant Colony Optimization and Genetic Algorithm by Qing Huang, Heru Xue, Jiangping Liu, Xinhua Jiang

“…Wavelength selection is one of the key steps in quantitative spectral analysis, which reduces the computation time while also improving the prediction accuracy of the model. In this paper, we propose a wavelength selection algorithm based on the ant colony optimization (ACO), in which the absolute value of the regression coefficient of the multiple linear regression (MLR) model is used as the basis for evaluating the importance of wavelengths, and the absolute value of the regression coefficient after full wavelength MLR modeling is used as the initial pheromone value of the ant colony optimization (MLR-ACO). …”
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Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803 by Namrata Bhagat, Guddu Kumar Gupta, Amritpreet Kaur Minhas, Deepak Chhabra, Pratyoosh Shukla

“…Furthermore, these machine learning tools can be used as a model to improve and optimize the yields for other metabolites production. …”
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A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. …”
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Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor by Jin Wang, Leishan Zhou, Yixiang Yue, Jinjin Tang, Zixi Bai

“…The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers.…”
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