A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

“…Subsequently, a scheduling optimization model is formulated to minimize both the system generation costs and the comprehensive risk, where the adaptive grid density-improved multi-objective particle swarm optimization (AG-MOPSO) algorithm is employed to efficiently generate Pareto-optimal operating point solutions. …”
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Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem by Junhee Lee, Heechan Chae, Seungwook Son, Jongwoong Seo, Yooil Suh, Jonguk Lee, Yongwha Chung, Daihee Park

“…Overcoming this limitation through large-scale labeling presents considerable burdens in terms of time and cost. To address the degradation issue, this study proposes a self-training-based domain adaptation method that utilizes a single label on target (SLOT) sample from the target domain, a genetic algorithm (GA)-based data augmentation search (DAS) designed explicitly for SLOT data to optimize the augmentation parameters, and a super-low-threshold strategy to include low-confidence-scored pseudo-labels during self-training. …”
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Facilitating real-time LED-based photoacoustic imaging with DenP2P: An optimized conditional generative adversarial deep learning solution by Avijit Paul, Srivalleesha Mallidi

“…Signal quality can be improved by traditional noise removal algorithms, but deep learning models outperform non-learning methods. …”
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Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. In the second stage, based on the estimated time parameters, path choice prior probabilities and observed data are combined using maximum likelihood estimation to infer the most probable paths among candidate routes. …”
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A carbon aware ant colony system for the sustainable generalized traveling salesman problem by Marina Lin, Laura P. Schaposnik

“…Our algorithm’s unique bi-objective optimization represents a significant advancement in sustainable transportation solutions strategically balancing cost and carbon emissions to reduce energy consumption and promote environmental responsibility.…”
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Simulating Methylamine Using a Symmetry-Adapted, Qubit Excitation-Based Variational Quantum Eigensolver by Konstantin M. Makushin, Aleksey K. Fedorov

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Bayesian-optimized ensemble deep learning models for demand forecasting in the volatile situations: A case study of grocery demand during Covid-19 outbreaks by Nader AL Theeb, Hazem Smadi, Naser Al-qaydeh

“…Furthermore, using BO algorithm for hyperparameters tuning improved the forecasting accuracy. …”
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Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…Traditional heuristic algorithms are limited in scalability and struggle to address the increasingly complex optimization problems of DNP. …”
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PARAMETRIC SYNTHESIS OF MODELS FOR MULTICRITERIAL ESTIMATION OF TECHNOLOGICAL SYSTEMS by Vladimir Beskorovainyi

“…The experimental study of the method confirms the increase in the efficiency of the procedures of parametric synthesis of models built on its basis in comparison with the method of group accounting of arguments on the basis of genetic algorithms. Practical application of the results obtained in the support systems for making multicriteria design and management decisions will improve their accuracy and, on this basis, increase the functional and cost efficiency of modern TS.…”
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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Therefore, this study took Liyang City as the study area, reconstructed Sentinel-2 cloud-free time series optical images, and extracted spectral features, vegetation indexes, and other features, in combination with the polarization features of the Sentinel-1 time series radar images. The optimal feature subset was selected through the feature selection method, and machine learning algorithms were optimized for paddy rice planting area classification. …”
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Yield Diagnosis and Tuning for Emerging Semiconductors During Research Stage by Chunshan Wang, Zizhao Ma, Yuxuan Zhu, Chensheng Jin, Dongyu Chen, Chuxin Zhang, Yining Chen, Wenzhong Bao, Yufeng Xie

“…The process of taking a new semiconductor device from the lab to the factory involves a lot of time, funds and manpower, a large portion of which is spent on device yield improvement. In recent years new methods have been tried to rapidly improve yields and using machine learning (ML) algorithms is one option. …”
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Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve... by Yunfei Li, Dongni Zhang, Yiren Wang, Yiren Wang, Yiheng Hu, Zhongjian Wen, Zhongjian Wen, Cheng Yang, Ping Zhou, Wen-Hui Cheng

“…ObjectiveThis study aimed to develop a risk prediction model for post-treatment oligometastasis in nasopharyngeal carcinoma (NPC) by integrating pathomics features and an improved Support vector machine (SVM) algorithm, offering precise early decision support.MethodsThis study retrospectively included 462 NPC patients, without or with oligometastasis defined by ESTRO/EORTC criteria. …”
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Optimal Power Flow for High Spatial and Temporal Resolution Power Systems with High Renewable Energy Penetration Using Multi-Agent Deep Reinforcement Learning by Liangcai Zhou, Long Huo, Linlin Liu, Hao Xu, Rui Chen, Xin Chen

“…A heterogeneous multi-agent proximal policy optimization (H-MAPPO) DRL algorithm is introduced for multi-area power systems. …”
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Improving health-promoting workplaces through interdisciplinary approaches. The example of WISEWORK-C, a cluster of five work and health projects within Horizon-Europe by Deborah De Moortel, Michelle C Turner, Ella Arensman, Alex Binh Vinh Duc Nguyen, Víctor Gonzalez

“…These shifts are giving rise to new forms of work (eg, hybrid work, gig economy jobs) and reshaping management and work organization practices (eg, through algorithmic decision-making or digital monitoring of worker performance). …”
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Improving accessibility to radiotherapy services in Cali, Colombia: cross-sectional equity analyses using open data and big data travel times from 2020 by Luis Gabriel Cuervo, Carmen Juliana Villamizar, Daniel Cuervo, Pablo Zapata, Maria B. Ospina, Sara Marcela Valencia, Alfredo Polo, Ángela Suárez, Maria O. Bula, J. Jaime Miranda, Gynna Millan, Diana Elizabeth Cuervo, Nancy J. Owens, Felipe Piquero, Janet Hatcher-Roberts, Gabriel Dario Paredes, María Fernanda Navarro, Ingrid Liliana Minotta, Carmen Palta, Eliana Martínez-Herrera, Ciro Jaramillo, on behalf of the AMORE Project Collaboration

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Energy Management of Plug-In Hybrid Electric Vehicles for Autonomous Driving in a Following Environment Based on Fuzzy Adaptive PID Control by Jixin Wang, Yujin Zhou

“…Therefore, this study is based on a fuzzy adaptive proportional integral differential controller, combined with an improved Cuckoo search algorithm, to perform group optimization on various parameters of the control system. …”
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Optimal Sizing, Techno-Economic Feasibility and Reliability Analysis of Hybrid Renewable Energy System: A Systematic Review of Energy Storage Systems’ Integration by Akhlaque Ahmad Khan, Ahmad Faiz Minai, Rakesh Kumar Godi, Vijay Shankar Sharma, Hasmat Malik, Asyraf Afthanorhan

“…The findings show that integrating HRES with ESS can lead to more sustainable energy systems, providing a long-term, reliable, and cost-effective solution. Findings emphasize the need for further study of optimization methods, meta-heuristic algorithm strategies, system components, design constraints, and desired techniques.…”
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On differential privacy for federated learning in wireless systems with multiple base stations by Nima Tavangaran, Mingzhe Chen, Zhaohui Yang, José Mairton B. Da Silva Jr., H. Vincent Poor

“…To find the locally optimal solutions of this problem, we first propose an algorithm that schedules the resource blocks and users. …”
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A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images by Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza, Jamel Baili, Dina Abdulaziz AlHammadi, Hee-Chan Cho, Byoungchol Chang

“…Two novel architectures, Sparse Convolutional DenseNet201 with Self-Attention (SC-DSAN) and CNN-GRU, are fused at the network level using a depth concatenation layer, avoiding the computational costs of feature-level fusion. Bayesian Optimization (BO) is employed for dynamic hyperparameter tuning, and an Entropy-controlled Marine Predators Algorithm (EMPA) selects optimal features. …”
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An intelligent incentive-based demand response program for exhaustive environment constrained techno-economic analysis of microgrid system by Bishwajit Dey, Gulshan Sharma, Pitshou N. Bokoro, Soham Dutta

“…Abstract The cost-effective scheduling of distributed energy resources through sophisticated optimization algorithms is the main focus of recent work on microgrid energy management. …”
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