Research on Indoor Object Detection and Scene Recognition Algorithm Based on Apriori Algorithm and Mobile-EFSSD Model by Wenda Zheng, Yibo Ai, Weidong Zhang

“…The specific research contents are as follows: (1) To address complex indoor scenes and occlusion, this paper proposes an improved Mobile-EFSSD object detection algorithm. An optimized MobileNetV3 with ECA attention is used as the backbone. …”
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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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Sensor placement optimization for critical-grid coverage problem of indoor positioning by Hui Wu, Zhe Liu, Jin Hu, Weifeng Yin

“…Then, NSGA-II algorithm was used to solve the optimizing model of sensor placement. …”
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Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm by Anqi Xu, Hui Li, Yun Hong, Guoji Liu

“…As the complexity of air gaming scenarios continues to escalate, the demands for heightened decision-making efficiency and precision are becoming increasingly stringent. To further improve decision-making efficiency, a particle swarm optimization algorithm based on positional weights (PW-PSO) is proposed. …”
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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…Accurate power load forecasting plays an important role in smart grid analysis. To improve the accuracy of forecasting through the three-level “decomposition–optimization–prediction” innovation, this study proposes a prediction model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the improved sparrow search algorithm (ISSA), a convolutional neural network (CNN), and bidirectional long short-term memory (BiLSTM). …”
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Study on the optimization of duration for repetitive projects considering spatial interference effects in operations by Chunli Zhang, Fan Zhang, Shuwen Yin, Yan Fu, Jun Liu, Peng Duan

“…Furthermore, we propose a model for solving optimal duration based on simulation results, using a genetic algorithm, and analyze the calculation results, speed, and complexity of the genetic algorithm with a heuristic approach. …”
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An Environmentally Adaptive CRO-SL Algorithm Based on Dynamic Agents for the Channel Assignment Problem in Wireless Networks by Antonio J. Romero-Barrera, Luis Cruz-Piris, Marino Tejedor-Romero, Jose Manuel Gimenez-Guzman, Ivan Marsa-Maestre

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Innovative Hybrid Algorithm for Solving Vehicle Routing Problem with Time Window by A.M. Rahimi, B. Yadegari, M. Aboutalebi Esfahani

“…The proposed algorithm is suitable for transportation and logistics systems with limited customers and leads to cost reduction, improved delivery times, and increased service quality.…”
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Improved MobileVit deep learning algorithm based on thermal images to identify the water state in cotton by Kaijun Jin, Jihong Zhang, Ningning Liu, Miao Li, Zhanli Ma, Zhenhua Wang, Jinzhu Zhang, Feihu Yin

“…This study introduces a method for identifying the moisture state of cotton using an enhanced MobileVit deep learning algorithm. This approach incorporates the Efficient Channel Attention (ECA) mechanism into the Fusion component of the MobileVit model, optimizes the first convolution in the Fusion component by replacing it with Depthwise Separable Convolution (DsConv), and substitutes the Local representation with the MobileOne block. …”
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Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

“…This study presents a novel Fractional Whale Optimization Algorithm-Enhanced Support Vector Regression (FWOA-SVR) framework for solar energy forecasting, addressing the limitations of traditional SVR in modeling complex relationships within data. …”
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Comparative Study of Algorithms for the Conversion From Surface Mesh Models to Volume Mesh Models by Youxi Wang, Qi Pang, Meng Li, Yang Liu

“…In addition, the randomness of the HXT algorithm in mesh generation led to variations in results, which requires further optimization to improve the consistency and robustness of the algorithm. …”
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Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
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Smart energy management for revenue optimization and grid independence in an Indian RDS by T. Yuvaraj, M. Thirumalai, M. Dharmalingam, Sudhakar Babu Thanikanti, Sanjeevikumar Padmanaban

“…A comparative analysis with alternative optimization algorithms demonstrates HPOA’s superiority in convergence speed, computational efficiency, and energy cost reduction. …”
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Milling Machine Fault Diagnosis Using Acoustic Emission and Hybrid Deep Learning with Feature Optimization by Muhammad Umar, Muhammad Farooq Siddique, Niamat Ullah, Jong-Myon Kim

“…A convolutional neural network (CNN) based on the VGG16 architecture is utilized for spatial feature extraction, followed by a bidirectional long short-term memory (BiLSTM) network to capture the temporal dependencies of the scalograms. The genetic algorithm (GA) is used to optimize feature selection and ensure the selection of the most relevant features to further improve the model’s performance. …”
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Kinematic Constrained RRT Algorithm with Post Waypoint Shift for the Shortest Path Planning of Wheeled Mobile Robots by Sisi Liu, Zhan Zhao, Jun Wei, Qianqian Zhou

“…This paper presents a rapidly exploring random tree (RRT) algorithm with an effective post waypoint shift, which is suitable for the path planning of a wheeled mobile robot under kinematic constraints. …”
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Research on Optimal Site Selection for Offshore Wind Farms Substation by Yuan YANG, Xiang Tang, Yanli XIN

“…Site selection of offshore substation plays a vital role for wind farm investment cost. This paper presents a method for optimal substation site selection for offshore wind farms substation. …”
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an-QNA: An Adaptive Nesterov Quasi-Newton Acceleration-Optimized CMOS LNA for 65 nm Automotive Radar Applications by Unal Aras, Lee Sun Woo, Tahesin Samira Delwar, Abrar Siddique, Anindya Jana, Yangwon Lee, Jee-Youl Ryu

“…It includes an improved post-linearization (I_PL) technique to enhance the linearity. …”
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Short-Term Photovoltaic Power Forecasting Based on the VMD-IDBO-DHKELM Model by Shengli Wang, Xiaolong Guo, Tianle Sun, Lihui Xu, Jinfeng Zhu, Zhicai Li, Jinjiang Zhang

“…The model’s hyperparameters are optimized using the IDBO. …”
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Internet of Things Based Application Placement Technique in Fog Environment by N Malathy, M Ruba, S Vinothini

“…A pre-scheduling method is developed to efficiently allocate tasks by analyzing workflows to reduce computation delays and energy usage. Leveraging an Improved Memetic Algorithm (IMA), this strategy enables effective scheduling of parallel IoT workflows across fog and cloud servers, ensuring balanced resource utilization and enhanced scalability. …”
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