Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…Traditional deep learning (DL) models and decision tree (DT)-based algorithms have been widely employed for this purpose. …”
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Computer Course Design Plan for Film and Television Media Major by Shan Hui, Xiao Zhang, Tian Yang

“…In view of the excellent global optimization ability of GA and the defects of the BP algorithm itself, this work adopts the improved GA algorithm to optimize the BP network, and establishes an IGA-BP network combination model with higher prediction accuracy. …”
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Power Allocation Technology of Long Time Multi-Star Hopping Beam for LEO Satellite by Ziyi LIU, Xiaoning ZHANG, Zesong FEI

“…LEO satellites have superior development prospects due to their low cost, low latency and small path loss, and are widely used in IoT, B5G and other fields.For the LEO satellite and its coverage area will be in a moving state, a convex optimization-based long-time multi-star beam hopping power allocation algorithm was proposed to maximize the system capacity.Focused on the multi-star hopping beam scenario over a period of time, a system model was developed based on the long-time co-orbital multi-star hopping beam scenario and the long-time heterodyne multi-star hopping beam scenario respectively.The resource allocation algorithm was designed for the two long-time multi-star hopping beams with the weighted objective function as the optimization objective, considered the influence factors of inter-star interference, load balancing and inter-star resource allocation priority, a long-time skipping beam resource allocation algorithm based on convex optimization was proposed.The simulation results showed that the proposed scheme could improve the resource utilization of the system compared with the conventional schemes.…”
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Application of WCA-RBF Neural Network in Fault Diagnosis of Analog Circuits by Zhiwei Jin

“…The adaptive step size was improved in the wolf pack algorithm, the parameters of the radial basis function neural network were optimized based on the wolf pack algorithm, and a wolf pack algorithm optimized radial basis function neural network model was constructed. …”
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Secret key generation for reconfigurable intelligent surface‐assisted MISO multi‐user system by Kexin Liu, Mingliang Li, Kaizhi Huang, Zheng Wan, Qinlong Li, Xiaoli Sun, Xiaoming Xu, Liang Jin

“…Then, the difference convex‐successive convex approximation based alternating optimization algorithm is proposed to solve this optimization problem. …”
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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

“…The coordinated situation assessment results are used to match corresponding tactics and maneuver control quantities. 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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An Interpretable Method for Asphalt Pavement Skid Resistance Performance Evaluation Under Sand-Accumulated Conditions Based on Multi-Scale Fractals by Yuhan Weng, Zhaoyun Sun, Huiying Liu, Yingbin Gu

“…The performance of mainstream machine learning models is compared, and the eXtreme Gradient Boosting (XGBoost) model is optimized using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. …”
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Simulation of incremental update of electronic document information based on big data technology by Zhiyuan Jin, Qi Zhang, Tiejun Pan

“…The network structure optimization is mainly achieved by increasing the number of neurons in the hidden layer, and the BP algorithm and gradient descent method are used to iteratively calculate until the model converges, so as to improve the model’s ability to capture the dynamic features of incremental data. …”
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Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

“…Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. …”
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Sparse Convolution FPGA Accelerator Based on Multi-Bank Hash Selection by Jia Xu, Han Pu, Dong Wang

“…However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. …”
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Passenger Flow Prediction of Integrated Passenger Terminal Based on K-Means–GRNN by Yifan Tan, Haixu Liu, Yun Pu, Xuemei Wu, Yubo Jiao

“…In this paper, the passenger flow GRNN prediction model is proposed, based on the K-means cluster algorithm, and an improved index named BWPs (Between-Within Proportion-Similarity) is proposed to improve the clustering effect of K-means so that the clustering effect of the new index is verified. …”
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A Two-Step Approach for Airborne Delay Minimization Using Pretactical Conflict Resolution in Free-Route Airspace by Ramazan Kursat Cecen, Cem Cetek

“…According to this comparison, both metaheuristics algorithms produce near optimal solutions in a reasonably short time. …”
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A Method for Enhancing the Traffic Situation Awareness of Vessel Traffic Service Operators by Identifying High Risk Ships in Complex Navigation Conditions by Lei Zhang, Jiahao Ge, Floris Goerlandt, Lei Du, Tuowei Chen, Tingting Gu, Langxiong Gan, Xiaobin Li

“…First, the K-means clustering algorithm is improved using the Whale Optimization Algorithm (WOA) to adaptively cluster ships within a waterway, segmenting the traffic in the area into multiple ship clusters. …”
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Adaptive distributed stochastic deep reinforcement learning control for voltage and frequency restoration in islanded AC microgrids with communication noise and delay by Nima Mahdian Dehkordi, Vahab Nekoukar

“…Distinct from prior DRL applications, our method rigorously couples Lyapunov-based stability guarantees with DRL-based gain tuning, ensuring formal stability despite stochastic disturbances and model uncertainties. This hybrid framework facilitates real-time optimization of control policies, contributing to improved resilience and robustness under realistic network conditions. …”
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Basketball teaching methods based on 3D-Convolutional neural network by Chao Huang, Xian Wu

“…The classification accuracy of the combined model of this algorithm was larger at 0.925. Compared with traditional teaching methods, this approach quantitatively assesses students' technical levels and improves the relevance and scientific nature of teaching feedback.…”
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Intelligent design of Fe–Cr–Ni–Al/Ti multi-principal element alloys based on machine learning by Kang Xu, Zhengming Sun, Jian Tu, Wenwang Wu, Huihui Yang

“…Multi-principal element alloys (MPEAs), distinguished by their complex compositions and exceptional mechanical properties, pose significant challenges for conventional predictive approaches in mechanical property optimization. This study proposes an innovative intelligent optimization algorithm (OA) to refine feature selection in machine learning (ML) models, targeting the prediction of ultimate tensile strength (UTS) and fracture elongation (FE) in MPEAs. …”
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Electric Vehicle and Soft Open Points Co-Planning for Active Distribution Grid Flexibility Enhancement by Jie Fang, Wenwu Li, Dunchu Chen

“…It replaces the traditional energy storage model with this model and then solves the EV and SOP collaborative planning model using a second-order conical planning algorithm with the objective function of minimizing the annual integrated cost. …”
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Discussing the Construction of a Budget Management System Combining Multimedia Technology and Financial Risk Management by Xiaoyi Jiang

“…In the traditional support vector machine, when the test sample is located at the boundary point of the hyperplane, the judgment may be wrong. In the aspect of SVM model improvement, according to the discrimination method of SVM, the weighted K-nearest neighbor algorithm is introduced to redistinguish the qualified test samples in the feature space. …”
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A Study on Vector-Based Processing and Texture Application Techniques for 3D Object Creation and Visualization by Donghwi Kang, Jeongyeon Kim, Jongchan Lee, Haeju Lee, Jihyeok Kim, Jungwon Byun

“…In this research, data weight reduction, parallel processing, and polygon simplification algorithms were applied to optimize the 3D model generation speed. …”
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Iterative phase contrast CT reconstruction with novel tomographic operator and data-driven prior. by Stefano van Gogh, Subhadip Mukherjee, Jinqiu Xu, Zhentian Wang, Michał Rawlik, Zsuzsanna Varga, Rima Alaifari, Carola-Bibiane Schönlieb, Marco Stampanoni

“…Breast cancer remains the most prevalent malignancy in women in many countries around the world, thus calling for better imaging technologies to improve screening and diagnosis. …”
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