Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). …”
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Review: the application of deep reinforcement learning to quantitative trading in financial market by XU Bo, HE Yijun, WEN Jiancheng, LI Xiangxia

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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

“…Finally, the proposed algorithm is applied to a post-disaster rescue scenario, where the task allocation results further demonstrate its superior performance.…”
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A novel lightweight YOLOv8-PSS model for obstacle detection on the path of unmanned agricultural vehicles by Zhijian Chen, Yijun Fang, Jianjun Yin, Shiyu Lv, Farhan Sheikh Muhammad, Lu Liu

“…Compared to the original base network, it reduces the number of parameters by 55.8%, decreases the model size by 59.5%, and lowers computational cost by 51.2%. When compared with other algorithms, such as Faster RCNN, SSD, YOLOv3-tiny, and YOLOv5, the improved model strikes an optimal balance between parameter count, computational efficiency, detection speed, and accuracy, yielding superior results. …”
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A hybrid approach to predicting and classifying dental impaction: integrating regularized regression and XG boost methods by Asok Mathew, Pradeep K. Yadalam, Ahmed Radeideh, Shrouk Hady, Rona Swed, Reyyan Cheema, Majd Mousa AL-Mohammad, Mohammed Alsaegh, SR Shetty

“…The study aims to find a correlation between eruption and distance from the root apex to the lower border of the mandible. Our feature selection process utilizes ensemble learning algorithms integrated with regularized regression techniques to analyze various parameters. …”
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A Dynamic Adaptive Ensemble Learning Framework for Noninvasive Mild Cognitive Impairment Detection: Development and Validation Study by Aoyu Li, Jingwen Li, Yishan Hu, Yan Geng, Yan Qiang, Juanjuan Zhao

“…Finally, the accuracy and efficiency of the classification model were improved by optimizing the combination of base learners. …”
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METRICS FOR EVALUATING CONSISTENCY IN DISTRIBUTED DATASTORES by Galyna Zholtkevych

“…The goal of the research is investigation of the ability to develop such a program on the earlier stage of building distributed network and build some components of decision-making algorithm, which purpose is to build optimal network topology. …”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…However, most of these studies focused too much on improving performance and did not pay attention to the computational cost aspect. …”
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Finding the Shortest Path with Vertex Constraint over Large Graphs by Yajun Yang, Zhongfei Li, Xin Wang, Qinghua Hu

“…In this paper, we first propose a novel exact heuristic algorithm in best-first search way and then give two optimizing techniques to improve efficiency. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…The network’s hyperparameters are adjusted through Bayesian Optimization (BO). Utilization of frequency as a sequential variable handled by RNN is a distinguishing feature of our approach, which leads to the enhancement of dependability and cost efficiency. …”
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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

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MAB-Based Online Client Scheduling for Decentralized Federated Learning in the IoT by Zhenning Chen, Xinyu Zhang, Siyang Wang, Youren Wang

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Leveraging petrophysical and geological constraints for AI-driven predictions of total organic carbon (TOC) and hardness in unconventional reservoir prospects by Nandito Davy, Ammar El-Husseiny, Umair bin Waheed, Korhan Ayranci, Manzar Fawad, Mohamed Mahmoud, Nicholas B. Harris

“…Our optimized models achieved R2 (coefficient of determination) of 0.89 and RMSE (root-mean-square error) of 0.47 for TOC predictions and 0.90 and 34.8 for hardness predictions, reducing RMSE by up to 13.52% compared to the unconstrained model. …”
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A Minimal Path-Based Method for Computing Multistate Network Reliability by Xiu-Zhen Xu, Yi-Feng Niu, Can He

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Frequency Regulation Provided by Doubly Fed Induction Generator Based Variable-Speed Wind Turbines Using Inertial Emulation and Droop Control in Hybrid Wind–Diesel Power Systems by Muhammad Asad, José Ángel Sánchez-Fernández

“…To achieve such goals, we used the above-mentioned proposed controls (EI&P and PC) and optimally tuned them using the Student-Psychology-Based Algorithm (SPBA). …”
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Vibration Control of Wind Turbine Blade Based on Data Fitting and Pole Placement with Minimum-Order Observer by Tingrui Liu, Lin Chang

“…It not only ensures certain accuracy, but also greatly improves the speed of calculation. The Wilson method, developed on the basis of the blade momentum theory, is adopted to optimize the structural parameters of the blade, with all parameters fitted as general model Sin6 (Sum of Sine) fitting curves. …”
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Local Search-Based Metaheuristic Methods for the Solid Waste Collection Problem by Haneen Algethami

“…Local search methods, notably GLS, have significantly improved the route construction process. The nearest neighbour algorithm has often outperformed the Clarke and Wright's methods. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Using S-G smoothing filtering (S-G), multivariate scattering correction (MSC), standard normal transformation (SNV), second derivative (SD), reciprocal logarithm (LR) and continuum removal (CR) to preprocess the data, the spectral characteristics and their correlation with water content were analyzed. In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. …”
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