Predicting the Attraction and Retention of Customers in Sports Pools in Isfahan City Using a Decision Tree: Presenting a Data Mining-Based Model by Seyed Masoud Mirsaeidi, Davood Nasr Esfahani

“…To evaluate the features, two algorithms—Grasshopper Optimization Algorithm (GOA) and Simulated Annealing (SA)—were used for feature selection, while classification algorithms, specifically Decision Tree (DT) and K-Nearest Neighbors (KNN), were employed to classify and recognize customer behavior. …”
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Sparse Feature-Weighted Double Laplacian Rank Constraint Non-Negative Matrix Factorization for Image Clustering by Hu Ma, Ziping Ma, Huirong Li, Jingyu Wang

“…We also propose an efficient alternating iterative update algorithm to optimize the proposed model and provide a theoretical analysis of its performance. …”
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QoS Aware Service Scheduling Scheme for VANETs by Ajay Guleria, Kuldip Singh, Narottam Chand

“…They provide the requests to road side unit (RSU) while travelling. The job of RSU is to handle various requests in such a way so that the service ratio and the quality of service (QoS) is optimized. …”
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Channel-Hopping Using Reinforcement Learning for Rendezvous in Asymmetric Cognitive Radio Networks by Dongsup Jin, Minho Jang, Ji-Woong Jang, Gyuyeol Kong

“…This paper addresses the rendezvous problem in asymmetric cognitive radio networks (CRNs) by proposing a novel reinforcement learning (RL)-based channel-hopping algorithm. Traditional methods like the jump-stay (JS) algorithm, while effective, often struggle with high time-to-rendezvous (TTR) in asymmetric scenarios where secondary users (SUs) have varying channel availability. …”
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Cooperative Downloading in Mobile Ad Hoc Networks: A Cost-Energy Perspective by He Li, Yang Yang, Xuesong Qiu, Zhipeng Gao, Guizhen Ma

“…However, the efficiency, cost, and energy consumption of cooperative downloading are sensitive by content distribution, which is a challenge to get the optimal in mobile ad hoc networks. This paper proposes a cost distribution (OCD) algorithm and a content distribution algorithm based on auction (OCDA) for mobile ad hoc networks based on relative location of nodes and local optimization theory. …”
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Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

“…Faricimab demonstrated significant and sustained anatomical improvements, allowing for extended treatment intervals while maintaining disease stability. Future research should focus on refining AI models to improve predictive accuracy and assessing long-term outcomes to further optimize disease management. …”
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ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data. by Brett A McKinney, Bill C White, Diane E Grill, Peter W Li, Richard B Kennedy, Gregory A Poland, Ann L Oberg

“…The ReliefSeq implementation adapts the number of nearest neighbors (k) for each gene to optimize the Relief-F test statistics (importance scores) for finding both main effects and interactions. …”
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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…Feature selection was performed using the Lasso algorithm to identify the most predictive variables, which were subsequently incorporated into the radiomics-based neural network model. …”
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Embedded Hardware-Efficient FPGA Architecture for SVM Learning and Inference by B. B. Shabarinath, Muralidhar Pullakandam

“…While Sequential Minimal Optimization (SMO) has enhanced the efficiency of SVM training, traditional implementations still suffer from high computational cost. …”
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Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. …”
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Forest cover and canopy health mapping in Australian subalpine landscape: supervised machine learning models for Sentinel-2 and Landsat images by Weerach Charerntantanakul, Marta Yebra, Hilary Rose Dawson, Adrienne Beth Nicotra, Saul Alan Cunningham, Matthew Theodore Brookhouse

“…We tested random-forest (RF), support vector machine (SVM), and multiple linear regression (MLR) to find the algorithm that provides the best accuracy. Cross-validation experiments were undertaken to optimize the model configurations. …”
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Multi-time Scale Voltage-Reactive Power Control for Distribution Network with Distributed Generation by LIU Haotian, ZHENG Chuyu, LENG Yang, LI Qin, ZHANG Hua, CHEN Shidu, LI Jiayong

“…And for the voltage regulation, it can optimize the regulation target according to the voltage sensitivity and the regulation costs of each DG, and thus has better economic performance while adjusting voltages.…”
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Predicting the subclinical carotid atherosclerosis in overweight and obese patients using a machine learning model by D. V. Gavrilov, T. Yu. Kuznetsova, M. A. Druzhilov, I. N. Korsakov, A. V. Gusev

“…The introduction of such risk stratification algorithms into practice will increase the accuracy and quality of CVR prediction and optimize the system of preventive measures.…”
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Tactical Coordination-Based Decision Making for Unmanned Combat Aerial Vehicles Maneuvering in Within-Visual-Range Air Combat by Yidong Liu, Dali Ding, Mulai Tan, Yuequn Luo, Ning Li, Huan Zhou

“…Finally, an improved particle swarm optimization algorithm (I-PSO) is proposed, which enhances the optimization ability and real-time performance through the design of local social factor iterative components and adaptive adjustment of inertia weights. …”
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Dense Matching with Low Computational Complexity for Disparity Estimation in the Radargrammetric Approach of SAR Intensity Images by Hamid Jannati, Mohammad Javad Valadan Zoej, Ebrahim Ghaderpour, Paolo Mazzanti

“…Notably, unlike traditional local and global models, the computational complexity of the proposed approach remains stable as the input size or kernel dimensions increase while memory consumption stays low. Compared to a pyramid-based local normalized cross-correlation (NCC) algorithm and adaptive semi-global matching (SGM) models, the proposed method maintains good accuracy comparable to adaptive SGM while reducing processing time by up to 50% relative to pyramid SGM and achieving a 35-fold speedup over the local NCC algorithm with an optimal kernel size. …”
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Beamforming design for energy-constrained full-duplex two-way relaying system by Wei WANG, Liyuan AN, Guoan ZHANG, Shibing ZHANG

“…A beamforming design was proposed under simultaneous wireless information and power transfer (SWIPT) protocol.A utility optimization problem was considered aiming to maximize the harvested energy by jointly optimizing the beamforming matrix,the power splitting ratio at the relay and the transmit powers at the sources.Since the formulated joint optimization problem was nonconvex,it was difficult or even intractable to obtain the global optimal solution.To overcome this issue,the objective problem into three subproblems was decoupled which could be solved by the proposed semidefinite relaxation technique and the derived constraints activation solution,respectively.The solution was finally obtained with the proposed convergent iterative algorithm.Simulation results show that the proposed joint optimization scheme achieves the optimal performance.Compared with the traditional half-duplex (HD) algorithm,the proposed algorithm can obtain 2~3 times energy harvesting (EH) efficiency improvement,while the computational complexity increases slightly.…”
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A machine learning-based efficient anomaly detection system for enhanced security in compromised and maligned IoT Networks by Anita Punia, Manish Tiwari, Sourabh Singh Verma

“…We use HP Tuned Machine Learning Algorithms further for developing an anomaly detection model and optimization of them by implementing machine learning algorithms. …”
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A Distributed Resilience Enhancement Strategy for Multi-microgrids Based on System of Systems Architecture by Linxinyan LIN, Junpeng ZHU, Yue YUAN

“…Firstly, the energy exchange process of the multi-microgrid systems is modeled based on the SoS architecture, and the distributed optimization algorithm is used to solve the model, which ensures the privacy of user information. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The optimized algorithm is then used for video skilled movement detection processing to obtain cropped frame images. …”
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Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…YOLOv3 and a coal mine key position personnel unsafe behavior recognition method based on improved YOLOv7 and ByteTrack experienced missed detections and false positives based on enhanced images, while the proposed pedestrian detection algorithm effectively mitigated these issues.…”
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