Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

Get full text

A distributional reinforcement learning model for optimal glucose control after cardiac surgery by Jacob M. Desman, Zhang-Wei Hong, Moein Sabounchi, Ashwin S. Sawant, Jaskirat Gill, Ana C. Costa, Gagan Kumar, Rajeev Sharma, Arpeta Gupta, Paul McCarthy, Veena Nandwani, Doug Powell, Alexandra Carideo, Donnie Goodwin, Sanam Ahmed, Umesh Gidwani, Matthew A. Levin, Robin Varghese, Farzan Filsoufi, Robert Freeman, Avniel Shetreat-Klein, Alexander W. Charney, Ira Hofer, Lili Chan, David Reich, Patricia Kovatch, Roopa Kohli-Seth, Monica Kraft, Pulkit Agrawal, John A. Kellum, Girish N. Nadkarni, Ankit Sakhuja

Get full text

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. …”
Get full text

Optimization Design of Node Placement Manipulators Based on Working Area and Response Speed by Huang Zhiqiang, Duan Yuxing, Song Xiaowei, Wang Jie, Fu Mingwei, Sun Haoxiang, Li Gang

“…Based on the multi-objective particle swarm algorithm and the variable density method, the size optimization and lightweight design of the node-distributed manipulator arm are carried out. …”
Get full text

Enhancing retail operations: Dynamic fulfilment strategies in Omnichannel retail by Hümeysa İskender, Sinem Dayanıklı, Abdullah Hulusi Kökçam, Željko Stević, Safiye Turgay, Mahmut Baydaş, Jasmina Bunevska Talevska

“…This study explores the trend of in-store fulfillment in omnichannel retail, where nearby store inventories are utilized for online order fulfillment. This model presents advantages such as faster delivery, cost reduction, improved stock management, increased sales, and enhanced customer satisfaction. …”
Get full text

Optimizing the Joint Replenishment and Delivery Scheduling Problem under Fuzzy Environment Using Inverse Weight Fuzzy Nonlinear Programming Method by Yu-Rong Zeng, Lin Wang, Xian-Hao Xu, Qing-Liang Fu

Get full text

Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm by Mahvash Zarimeidani, Amir Amirabadi, Nasrin Amiri, Iman Ahanian, Siavash Es’haghi

“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
Get full text

Energy efficient adaptive clustering with QoS-aware CBRP and grey wolf optimization clustering algorithm for mobile ad-hoc network (MANET) by Minal Patil, Manish Chawhan, Roshan Umate, Abhishek Madankar, Bhumika Neole

Get full text

Development of a Mathematical Model and Structural Optimization of the Specific Resistance of a Broken Line Subsoiler by Da Qiao, Qian Shi, Pinyan Lv, Yingjie Guo, Daping Fu, Min Liu, Limin Jiang, Yang Wang, Jingli Wang, Weizhi Feng

“…Aiming at the problems of shallow subsoiling depth, large subsoiling specific resistance and small soil bulkiness in subsoiling operation in saline-alkali soil, this paper establishes a mathematical model of the specific resistance of a broken line subsoiler and uses genetic algorithm and the discrete element method to optimize the structure design of the subsoiler. …”
Get full text

A new Hybrid Metaheuristic Model for Image Edge Detection by Adil Khalil, Adel Abed Al Wahaab, Ahmed Abbas

“…These techniques may have the potential to provide advanced capabilities to improve the image edge detection process. A metaheuristic model such as the Bat algorithm may offer appropriate parameters for the edge detection algorithm. …”
Get full text

Improvement of Electronic Correspondence of Inter-enterprise with Service Component of ECES by Mohammad Hadi Emtehani, Sima Emadi

Get full text

Minimization of Material Waste Through Maintenance Interval Optimization in Transport Systems by Augustyn Lorenc, Małgorzata Kuźnar

“…Although the case study is based on railway vehicles, the approach is applicable to road, maritime, and air transport as well. By leveraging optimization algorithms, such as machine learning, this solution predicts optimal maintenance timing, thereby reducing resource consumption and improving operational efficiency. …”
Get full text

Three-dimensional design, simulation and optimization of a centrifugal compressor impeller with double-splitter blades by Mohammadjavad Tasharrofi, Mojtaba Heidarian Shahri, Ali Madadi

“…Since the optimization process only using genetic algorithms is very time-consuming and has high computational costs, artificial neural networks were used to reduce costs. …”
Get full text

Optimization of Offshore Saline Aquifer CO₂ Storage in Smeaheia Using Surrogate Reservoir Models by Behzad Amiri, Ashkan Jahanbani Ghahfarokhi, Vera Rocca, Cuthbert Shang Wui Ng

“…This research will demonstrate SRMs’ potential in long-term simulations and optimization of geological carbon storage in a real-world geological setting and address challenges in big data curation and model training. …”
Get full text

Optimization of trusted wireless sensing models based on deep reinforcement learning for ISAC systems by Hao Zhang, Yi Jing, Wenhui Xu, Ronghui Zhang

“…Abstract This paper investigates using deep reinforcement learning (DRL) methods for optimizing trustworthy federated learning models, with a focus on integrated sensing and communication in practical wireless sensing scenarios. …”
Get full text

Optimizing Deep Learning Models for Fire Detection, Classification, and Segmentation Using Satellite Images by Abdallah Waleed Ali, Sefer Kurnaz

“…The findings underscore the significant potential of optimized machine learning approaches in predicting extreme events, such as wildfires, and improving fire management strategies. …”
Get full text

Integrated production-distribution planning optimization models: A review in collaborative networks context by Beatriz Andres, Raquel Sanchis, Jaques Lamothe, Leila Saari, Frederic Hauser

“…In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. …”
Get full text

Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…This paper introduces the League of Legends Match Data Compactor (LoL-MDC), a tool designed to transform extensive match data into a concise and structured format optimized for LLM processing. By systematically summarizing structured match information—including match overviews, player and team statistics, timeline summaries, and algorithmically selected key events—the LoL-MDC significantly reduces the data size from approximately 80,000 tokens to under 2000 tokens while retaining analytical value. …”
Get full text

Efficient cooling capability in microchannel heat sink reinforced with Y-shaped fins: Based on artificial neural network, genetic algorithm, Pareto front, and numerical simulation by Xiang Ma, Ali Basem, Pradeep Kumar Singh, Rebwar Nasir Dara, Ahmad Almadhor, Amira K. Hajri, Raymond Ghandour, Barno Abdullaeva, H. Elhosiny Ali, Samah G. Babiker

“…A genetic algorithm was employed for single-objective optimization targeting three criteria: maximizing total efficiency, minimizing pressure drop, and maximizing the Nusselt number. …”
Get full text

A two stage differential evolution algorithm for parameter estimation of proton exchange membrane fuel cell by Mohammad Aljaidi, Sunilkumar P. Agrawal, Pradeep Jangir, Sundaram B. Pandya, Anil Parmar, Arpita, Ali Fayez Alkoradees, Bhargavi Indrajit Trivedi, Mohammad Khishe

“…Most traditional parameter estimation methodologies depend on optimization algorithms which are limited in their efficiency, convergence speed, and robustness. …”
Get full text