Recent Advances in Multi-Agent Reinforcement Learning for Intelligent Automation and Control of Water Environment Systems by Lei Jia, Yan Pei

“…This work aims to provide a theoretical foundation and key insights for advancing research and practical applications of MARL-based intelligent control in water infrastructure systems.…”
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Research on planning and demand matching strategies for intelligent material supply chains under carbon constraints by Shao Xuwei, Wu Jianfeng, Ge Junping, Wang Jianguo, Hu Kairui, Qiu Yang, Ju Chunhua, Xu Jiaming

“…This complex supply chain network makes it difficult for traditional optimization algorithms and path planning methods to effectively cope with the demand for low-carbon, efficient and flexible logistics. …”
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Enhanced Q learning and deep reinforcement learning for unmanned combat intelligence planning in adversarial environments by Xu Jianhong, Liang Gongqian

“…Abstract This study proposes a multimodal deep reinforcement learning (MDRL) architecture, Multimodal Deep Reinforcement Learning-Deep Q-Network (MDRL-DQN), based on an improved Q-Learning algorithm. It aims to optimize Unmanned Aerial Vehicle (UAV) scheduling and execution capabilities in intelligent unmanned combat planning. …”
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Healthcare Prediction Using Novel Machine Learning Methods and Metaheuristic Algorithm by Yazdan Ashgevari, Behrouz Alefy, Faranak Kazemi

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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…Abstract As a necessary part of intelligent control of a joint station, the automatic identification of abnormal conditions and automatic adjustment of operation schemes need to judge the running state of the system. …”
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Interpretable Prediction of a Decentralized Smart Grid Based on Machine Learning and Explainable Artificial Intelligence by Ahmet Cifci

“…This study addresses this challenge by leveraging machine learning (ML) models and explainable artificial intelligence (XAI) techniques to predict the stability of a decentralized smart grid. …”
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Development and Optimization of the Internet of Things Network for Product Quality Monitoring by U. А. Vishniakou, Hu Zhifeng

“…The application of intelligent algorithms for farm management is also considered: data processing and training ‒ ML, knowledge processing ‒ DT, security ‒ FL. …”
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An Artificial Plant Community Algorithm for Collision-Free Multi-Robot Aggregation by Zhengying Cai, Qingqing Yu, Zhuimeng Lu, Zeya Liu, Guoqiang Gong

“…Second, a heuristic artificial plant community algorithm is proposed to obtain an optimal solution to the developed problem model, which is lightweight and can be deployed on edge robots to search for the optimal route in real-time. …”
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Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization by Lianbo Ma, Hanning Chen, Kunyuan Hu, Yunlong Zhu

“…Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Intelligent management of medical appointments can significantly enhance patient care and reduce health risks. …”
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TAL-SRX: an intelligent typing evaluation method for KASP primers based on multi-model fusion by Xiaojing Chen, Xiaojing Chen, Jingchao Fan, Jingchao Fan, Shen Yan, Longyu Huang, Longyu Huang, Longyu Huang, Guomin Zhou, Guomin Zhou, Jianhua Zhang, Jianhua Zhang

“…To address the above problems, we proposed a typing evaluation method for KASP primers by integrating deep learning and traditional machine learning algorithms, called TAL-SRX. First, three algorithms are used to optimize the performance of each model in the Stacking framework respectively, and five-fold cross-validation is used to enhance stability. …”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Objective: To provide a comprehensive review on the existing research and evidence regarding artificial intelligence (AI) applications in the assessment and management of urinary stone disease. …”
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Possibilities of using artificial intelligence technologies in the morphological diagnosis of inflammatory bowel diseases (literature review) by E. G. Churilova, A. B. Kazumova, Kh. M. Akhrieva, N. V. Pachuasvili, A. S. Tertychnyy

“…This study focuses on the role of artificial intelligence (AI) in the morphological diagnosis of IBD, endoscopic visualization, outcome prediction, and patient monitoring. …”
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Rooster Colony Algorithm: A two-step Multi-Swarm Optimization Approach by Miguel A. Salido, Adriana Giret, Christian Perez, Carlos March

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Secure intelligent reflecting surface assisted mobile edge computing system with wireless power transfer by Dawei Wang, Xuanrui Li, Menghan Wu, Yixin He, Yi Lou, Yu Pang, Yi Lu

“…Moreover, we propose a dichotomy particle swarm algorithm based on the bisection method to process the overall optimization problem and improve the convergence speed. …”
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Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection by Mohammed Abdullah, Ryna Svyd

“…This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

“…Future research works involve extending the performance of the algorithms with new datasets, creating and optimizing embedded AI models, deploying edge-IoT with embedded AI for wearable devices, implementing an autonomous AI cloud engine, and implementing federated learning to deliver scalable smart health in a smart city context.…”
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Improved Firefly Algorithm Based on Heuristic Information by CUI Jia-rui, LI Qing, YANG Liu-yi, WANG Heng, ZHANG Bo-yu

“…Firefly Algorithm (FA) is an optimization algorithm based on swarm intelligence which mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies With the aim to address the disadvantages of the firefly algorithm of slow convergence speed and ease of falling into the local optimum in the later period of the evolution process, the firefly algorithm is improved herein Two kinds of heuristic information are proposed into the algorithm to guide the convergence of the algorithm The first one takes the current global best as the heuristic information referencing the “global optimal” idea in particle swarm optimization, therefore, an algorithm called FAGO (Firefly Algorithm based on Global Optimization) is formed The second one is called FABE (Firefly Algorithm based on Bayesian Estimation) using the optimal moving direction calculated by Bayesian estimation as heuristic information The improved algorithms in this study are applied to numerical simulations of several classical test functions and compared with traditional FA and some other′s research are carried out The simulation results show that the proposed algorithms can well accelerate the convergence speed and improve the convergence accuracy…”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…During model training, the Adam optimization algorithm is employed, and the model's performance is enhanced by introducing a customized dependency self-attention mechanism for parameter optimization. …”
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