Post-Processing Optimization of the Global 30 m Land Cover Dynamic Monitoring Product by Zhehua Li, Xiao Zhang, Wendi Liu, Tingting Zhao, Weitao Ai, Jinqing Wang, Liangyun Liu

“…Third, certain land cover transitions between easily misclassified types were optimized using logical rules and multi-source data. …”
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Analysis and Optimization of Micro Speaker-Box Using a Passive Radiator in Portable Device by Yuan-Wu JIANG, Joong-Hak KWON, Hyung-Kyu KIM, Sang-Moon HWANG

“…The Finite Element Method (FEM), two-degree-of-freedom (DOF) vibration theory, and a plane circular piston sound source were used to study the electromagnetic, vibration, and acoustic characteristics, respectively. …”
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SCSO: snake optimization with sine-cosine algorithm for parameter extraction of solar photovoltaic models by Qingrui Li, Yongquan Zhou, Qifang Luo

“…The proposed algorithm incorporates three key improvements: (1) integration of the Sine–Cosine Algorithm to enhance the bio-inspired Snake Optimization, balancing exploration and exploitation; (2)The parameters C 1 and C 2 are adaptively adjusted, and the Newton–Raphson method is introduced to accelerate the algorithm’s convergence speed which accelerates convergence; and (3) application of a lens imaging reverse learning strategy to improve exploration capabilities and population diversity, preventing the algorithm from becoming trapped in local optima. …”
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A novel framework for optimizing residential load response planning with consideration of user satisfaction by Mohammad Hossein Erfani Majd, Gholam-Reza Kamyab, Saeed Balochian

“…The primary objective is to minimize electricity costs while ensuring efficient use of renewable energy resources. The proposed method utilizes the Meerkat Optimization Algorithm (MOA), which is compared against other optimization algorithms, including Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Teaching-Learning-Based Optimization (TLBO). …”
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Research on the optimal operation of a prosumer micro energy network centred on data centres by Yuanshi Zhang, Yiwu Ge, Shunjiang Wang, Weiqi Pan, Yiwen Feng, Peng Qiu

“…By considering data interaction and power sharing among multiple micro‐energy networks, the alternating direction method of multipliers algorithm is used to solve the system‐distributed optimization problem in two stages. …”
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Optimization planning of new rural multi-energy distribution network based on fuzzy algorithm by Huanhuan Ye, Qing Wang, Yongsheng Xian, Bo Wen, Yuange Li, Siwei Hou

“…Existing methods are difficult to cope with the volatility and uncertainty of energy sources, resulting in uneven load distribution, high energy loss and low system efficiency. …”
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An incremental data-driven approach for carbon emission prediction and optimization of heat treatment processes by Qian Yi, Xin Wu, Junkang Zhuo, Congbo Li, Chuanjiang Li, Huajun Cao

“…In manufacturing enterprises, the variety of heat treatment processes, insufficient data in the early stages of production, and the continuous increase of samples over time make it difficult to predict and optimize carbon emissions dynamically. Therefore, this paper proposes a low-carbon optimization method for heat treatment processes based on incremental data-driven approaches. …”
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Multi-Time Scale Coordinated Optimization of Energy Systems Under Flexible Load Response by Jinfeng Gao, Daifeng Gao, Chun Xiao

“…To address these challenges, this study investigates multi-time scale collaborative optimization of energy systems based on flexible load response, utilizing a combination of qualitative and quantitative methods. …”
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Predicting carbon dioxide emissions using deep learning and Ninja metaheuristic optimization algorithm by Anis Ben Ghorbal, Azedine Grine, Ibrahim Elbatal, Ehab M. Almetwally, Marwa M. Eid, El-Sayed M. El-Kenawy

“…Experimental results also demonstrate that the proposed NiOA-DPRNNs framework gets the highest value of R2 (0.9736), lowest error rates and fitness values than other existing models and optimization methods. From the Wilcoxon and ANOVA analyses, one can approve the specificity and consistency of the findings. …”
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Evaluating soiling effects to optimize solar photovoltaic performance using machine learning algorithms by Muhammad Faizan Tahir, Anthony Tzes, Tarek H.M. El-Fouly, Mohamed Shawky El Moursi, Nauman Ali Larik

“…Hyperparameter optimization using Bayesian methods enhances predictive performance. …”
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Optimizing integration techniques for UAS and satellite image data in precision agriculture — a review by Aliasghar Bazrafkan, C. Igathinathane, Nonoy Bandillo, Paulo Flores

“…This review explores the significance of integrating high-resolution UAS and satellite imagery via pixel-based, feature-based, and decision-based fusion methods. The study investigates optimization techniques, spectral synergy, temporal strategies, and challenges in data fusion, presenting transformative insights such as enhanced biomass estimation through UAS-satellite synergy, improved nitrogen stress detection in maize, and refined crop type mapping using multi-temporal fusion. …”
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APPLICATION OF MATHEMATICAL MODELING OF THE AIRCRAFT STRUCTURES STRESS STATE TO OPTIMIZE CORROSION DAMAGE REMOVAL by D. P. Saidzhanov, V. V. Efimov

“…However, it is impossible to refuse the removal of corrosion damage, but it is possible to optimize the stripping area parameters. The purpose of this paper is to solve the problem by applying mathematical modeling of the aircraft structures stress state by using open source software based on a finite element method (FEM). …”
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Search direction optimization of power flow analysis based on physics-informed deep learning by Baoliang Li, Qiuwei Wu, Yongji Cao, Changgang Li

“…Power flow analysis is crucial for obtaining power system operation states and optimizing control measures. The increasing integration of renewable energy sources has resulted in a more complex power system, posing challenges to the computational efficiency and convergence of conventional power analysis methods. …”
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Sunflower-based butterfly optimization algorithm with enhanced RNN for the harmonics elimination in multilevel inverter by V. Mohan, G. Krithiga, M. Thamil Alagan, V. Sathya

“…In this paper, the Sunflower based– Butterfly Optimization Algorithm (SF-BOA) is presented as a method for evaluating transcendental nonlinear equations using an MLI in a SHE approaches. …”
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Auto regressive neural network-driven reliability optimization in base-isolated building design by John Thedy, Kuo-Wei Liao, Taeyong Kim

“…Trained on various ground motions and Nonlinear Time History Analysis (NLTHA) data, the ARNN produces full response histories, unlike prior methods focused solely on peak responses. A Single Degree of Freedom (SDOF) example demonstrates ARNN accuracy, and a four-story base-isolated building is used for a Reliability-Based Design Optimization (RBDO) case study. …”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…Different from forward selection or linear optimization, which could have low efficiency for complicated problems with large sample size and multiple objectives, new methods and algorithms for NP-hard problems would be necessary to be investigated. …”
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The Application of Graph Neural Networks in Power Systems from Perspective of Perception-Prediction-Optimization by Zhuo LI, Yinzhe WANG, Lin YE, Yadi LUO, Xuri SONG, Zhenyu ZHANG

“…Conventional data analysis methods for Euclidean space often exhibit poor performance and low accuracy when representing the topological structures relationship with multi-source heterogeneous and irregular characteristics. …”
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Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

“…One significant branch of modern control algorithms concerns reinforcement learning, a data-driven strategy capable of dynamically managing renewable energy sources and other energy subsystems under uncertainty and real-time constraints. …”
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Research on optimization technology of new pipeline design for regional natural gas pipeline network by Jingyi CUI, Kunfeng ZHU, Cuixian GAO, Li GU, Jing REN, Yuxing LI, Wuchang WANG

“…To meet future gas demand and enhance the efficiency of pipeline design, it is essential to review and analyze existing pipeline planning and design methods, as well as optimization algorithms. There is an urgent need to develop a set of design optimization methods suitable for complex pipeline network systems with multiple gas sources, numerous users, and aging pipeline infrastructures. …”
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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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