Model-Predicted Control System for the Real-Time Operation of an Urban Drainage System to Mitigate Urban Flood Risk: A Case Study in the Liede River Catchment, Guangzhou, China by Xing Quan, Zhile Chen, Tao Jiang, Weifei Liu, Yaojun Mo, Bing Chen

“…By comparing the results of three control scenarios (i.e., the original control scenario, the current MPC, and the ideal MPC) under three typical rainfall events, the results demonstrate that the MPC system can effectively mitigate urban flood risk in engineering applications and the decision-making of the MPC system is valid. …”
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Joint Resource Scheduling of the Time Slot, Power, and Main Lobe Direction in Directional UAV Ad Hoc Networks: A Multi-Agent Deep Reinforcement Learning Approach by Shijie Liang, Haitao Zhao, Li Zhou, Zhe Wang, Kuo Cao, Junfang Wang

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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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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…The data in the spectral raw bands were optimized using convolutional smoothing (S-G), standard normal variable transformation (SNV), multiplicative scatter correction (MSC), and baseline calibration (baseline) algorithms, respectively. In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Research on Impact of Planned Path Length and Yaw Cost on Collaborative Search of Unmanned Aerial Vehicle Swarms by Heng Zhang, Wenyue Meng, Yanan Liu, Guanyu Liu, Jian Zhang

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Site Selection of Offshore Wind Power-Hydrogen Production and Refueling Ports Based on Empirical Mining and Hybrid Linguistic Approach by Ningbo HUANG, Jianwei GAO, Chuanbo XU, Xuanhua XU, Shutong ZHAO, Xunjie GOU, Xiaojing JIANG

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Extracting Target Detection Knowledge Based on Spatiotemporal Information in Wireless Sensor Networks by Tian Wang, Zhen Peng, Cheng Wang, Yiqiao Cai, Yonghong Chen, Hui Tian, Junbin Liang, Bineng Zhong

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Optimizing Competency-Based Human Resource Allocation in Construction Project Scheduling: A Multi-Objective Meta-Heuristic Approach by Bahman Shojaei, Heidar Dashti Naserabadi, Mohammad Javad Taheri Amiri

“…This paper addresses the challenge of competency-based workforce allocation in construction project scheduling by integrating multi-criteria decision-making with meta-heuristic optimization. A three-objective mathematical planning model aimed at minimizing project completion time, reducing implementation costs, and enhancing workforce competency is proposed. …”
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Modified Index Policies for Multi-Armed Bandits with Network-like Markovian Dependencies by Abdalaziz Sawwan, Jie Wu

“…Sequential decision-making in dynamic and interconnected environments is a cornerstone of numerous applications, ranging from communication networks and finance to distributed blockchain systems and IoT frameworks. …”
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Chemical Properties of Heterogenous Catalysts in Improving Yield of Biofuel Production by Qian Yanfei

“…It systematically optimizes hub layouts, flexible resource allocation, and dynamic control by employing spatial topology algorithms, multi-agent game models, and digital twin technology.A three-tier toolkit comprising “model classification,” “algorithm adaptation,” and “scenario application” has been developed to address issues such as facility layout mismatches, inefficient resource scheduling, and limited resilience to sudden surges in passenger flow.Empirical evidence indicates that, following optimization, the distance between subway and bus connections is reduced to 150 meters, decreasing transfer time by 40%. …”
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User preferences in multi-objective routes: The role of gradient visualization and personality measures. by Keisuke Otaki, Takayoshi Yoshimura

“…These pairs were generated using a multi-objective planning algorithm that optimizes both attributes. Our findings reveal three key insights. …”
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Ensemble-Based Neighborhood Attribute Reduction: A Multigranularity View by Yuan Gao, Xiangjian Chen, Xibei Yang, Pingxin Wang, Jusheng Mi

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Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

“…A recently proposed on‐policy actor–critic method, phasic policy gradient (PPG) which extends the proximal policy optimization algorithm with an auxiliary optimization phase to improve training by distilling features from the critic to the actor network, is used to make EVCS decisions on the network where EV travels through the optimal path from origin node to EVCS by considering dynamic traffic conditions, unit value of EV owner and time‐of‐use charging price. …”
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A Reliable Approach for Solving Transmission Network Expansion Planning with Objective of Planning Cost Reduction by Yongqiu Liu

“…The particle swarm optimization algorithm searches for optimal planning to reach the fitness requirement. transmission expansion planning problem involves a decision on the location and number of new transmission lines. …”
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Comparative Analysis of Neutrosophic, Pythagorean neutrosophic, and Fermatean neutrosophic Soft Matrices in the context of Industrial Accidents: A Case Study by Smruthi P, Abinaya S, Dharunya S, R. Sun dareswaran, Shanmugapriya M, Said Broumi

“…This study presents a comparative analysis of three plithogenic frameworks—Neutrosophic soft sets, Pythagorean neutrosophic soft sets, and Fermatean neutrosophic soft sets—aiming to model and analyze industrial accidents. …”
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A hybrid unsupervised machine learning model with spectral clustering and semi-supervised support vector machine for credit risk assessment. by Tao Yu, Wei Huang, Xin Tang, Duosi Zheng

“…The proposed algorithm is anticipated to expand the customer base for financial institutions while reducing economic losses.…”
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Diagnostic of fatty liver using radiomics and deep learning models on non-contrast abdominal CT. by Haoran Zhang, Jinlong Liu, Danyang Su, Zhen Bai, Yan Wu, Yuanbo Ma, Qiuju Miao, Mingyue Wang, Xiaopeng Yang

“…Two-dimensional (2D) and three-dimensional (3D) radiomics models, as well as 2D and 3D deep learning models, were developed, and machine learning models based on clinical data were constructed for the four-category diagnosis of fatty liver. …”
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Method for recognizing abnormal operation patterns in hydraulic support machine-following and shifting control by MA Zhitao, FU Xiang, LI Haojie, NIU Penghao, JIA Yifan

“…A decision tree model was employed to detect stroke anomaly patterns. …”
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Cooperative Spectrum Sensing for Cognitive Heterogeneous Networking Using Iterative Gauss-Seidel Process by Haleh Hosseini, Kaamran Raahemifar, Sharifah Kamilah Syed Yusof, Alagan Anpalagan

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WEIGHTED ADDITIVE MODEL AND CHANCE CONSTRAINED TECHNIQUE FOR SOLVING NONSYMMETRICAL STOCHASTIC FUZZY MULTIOBJECTIVE LINEAR PROGRAM by Grandianus Seda Mada, Nugraha K.F. Dethan, Fried Markus Allung Blegur, Adriano Dos Santos

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