Music genre classification with parallel convolutional neural networks and capuchin search algorithm by Yuxin Zhang, Teng Li

“…The method makes use of discrete wavelet transform (DWT), mel frequency cepstral coefficients (MFCC), and short-time fourier transform (STFT) characteristics to provide a comprehensive framework for expressing stylistic qualities in music. To do this, each model’s hyperparameters are generated using the capuchin search algorithm (CapSA). …”
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Defense Methods for Adversarial Attacks Against Power CPS Data-Driven Algorithms by Weiping ZHU, Yi TANG, Xingshen WEI, Zengji LIU

“…In response to the potential adversarial attacks on data-driven algorithms in power CPS, this paper proposes corresponding defense methods from such three aspects as abnormal data filtering and recovery, algorithm vulnerability mining and optimization, and algorithm self interpretability improvement: abnormal data filter, GAN-based vulnerability mining and optimization method, data knowledge fusion model and its training method. …”
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Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Yuzhu Luo, Jiarong Wang, Ming Wei

“…From the standard feedforward wavelet neural network algorithm using global optimization capabilities, we improve the wolf pack algorithm, improve the search accuracy of the algorithm, get the best solution of the estimated value of the work according to the search results when completing the research objectives, and get the ability to predict the work of the model. …”
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Optimizing power network expansion with pumped hydro energy storage using a multi-objective enhanced spider wasp optimizer approach by Mohamed M. Refaat, Saad F. Al-Gahtani, Hussain Bassi, Ziad M. Ali, Shady H. E. Abdel Aleem

“…The problem is framed as a comprehensive multi-objective optimization model designed to minimize the cost of network expansion while maximizing the benefits of integrating various PHES technologies. …”
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Research of Online Error Prediction and Parallel Algorithm for Voltage Transformer in Smart Grid by Xin Xianfeng, Chen Rongye, Lin Cong, Liu Qingchan, He Zhaolei, Li Tengbin, Yang Guangrun, Kochan Orest, Karpa Mykhailo

“…This article mainly focuses on the online error prediction and the parallelization method of voltage transformers. First, an optimized multi-layer perceptron model based on the sparrow search algorithm (SSA) is proposed. …”
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Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database by Hongyi Chen, Haiyang Song, Hongyu Huang, Xiaojun Fang, Huang Chen, Qingqing Yang, Junyu Zhang, Wenjun Ding, Zheng Gong, Jun Ke

“…Rapid and accurate diagnosis is pivotal for improving patient survival rates.MethodsWe developed a machine learning prediction model using the MIMIC-IV database (n = 14,716 patients, including 1,302 high-risk cases). …”
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Train adaptive energy saving strategy based on iterative induced genetic algorithm by MEI Wenqing, SHI Ke, ZHANG Zhengfang

“…Then, to overcome the difficulty of traditional genetic algorithms in solving continuous sub-interval optimization problems due to discrete independence, an iterative induced genetic algorithm was designed to calculate the Pareto optimal solution set for the energy-saving objective function. …”
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The necessity of the Black Sea region transport structure improvement by L.V. Nazarova

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Artificial Intelligence Algorithms for Hybrid Electric Powertrain System Control: A Review by Dawei Zhong, Bolan Liu, Liang Liu, Wenhao Fan, Jingxian Tang

“…In recent years, artificial intelligence algorithms have provided new solutions for the intelligent control of hybrid electric powertrain systems with their powerful nonlinear modeling capabilities, data-driven optimization, and adaptive learning capabilities. …”
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A Detailed Comparison of Two New Heuristic Algorithms Based on Gazelles Behavior by Emine Baş

“…In this study, Mountain Gazelle Optimization (MGO) and Gazelle Optimization Algorithm (GOA) algorithms, which have been newly proposed in recent years, were examined. …”
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The integration of artificial intelligence in assisted reproduction: a comprehensive review by Pragati Kakkar, Shruti Gupta, Kasmiria Ioanna Paschopoulou, Ilias Paschopoulos, Ioannis Paschopoulos, Vassiliki Siafaka, Orestis Tsonis

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Energy scheduling algorithm for urban rail active traction power supply system by ZHANG Chao, LI Hongbo, ZHAO Liying, HUANG Zihao, LUO Wenguang, WANG Xiong

“…The full power and constant voltage models were used to simulate the two different working conditions of the bidirectional converter, and the internal and external double-layer iterative algorithm was used to calculate the power flow. …”
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Anomaly detection using unsupervised machine learning algorithms: A simulation study by Edmund Fosu Agyemang

“…Future work should explore parameter optimization, the impact of dataset characteristics on model performance, and the application of these models to real-world datasets to validate their efficacy in practical anomaly detection scenarios.…”
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Application of artificial intelligence technology in the economic development of urban intelligent transportation system by Ziming Zhao, Jinyu Chen

“…A traffic flow prediction model was established for traffic flow prediction and optimized scheduling algorithms were used to dispatch vehicles on congested urban roads intelligently. …”
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Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

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Image Reconstruction Algorithm Based on Extreme Learning Machine for Electrical Capacitance Tomography by SU Ziheng, CHEN Deyun, WANG Lili

“…Aiming at the problem that the traditional ECT is not accurate in complex situations, this paper proposes a depth learning based inversion method Through the improvement and optimization of the traditional extreme learning machine, the image feature information obtained by the reconstructed image method is used as the training data, and the result obtained by inputting the data into the predictive model is used as the prior information The cost function is used to encapsulate the prior knowledge and domain expertise, and spatial regularizers and time regularizers are introduced to enhance sparsity The separated Bregman (SB) algorithm and the iterative shrinkage threshold (FIST) method are used to solve the specified cost function The final imaging result is obtained The simulation results show that the image reconstructed by this method has less than 10% error compared with the original flow pattern, and reduces artifacts and distortion, which improves the reconstructed image quality…”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. …”
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A hybrid Spatial Ant Lion optimization and utilitarian data transmission approach for intelligent optimization for energy-efficient wireless sensor networks by Malathy Sathyamoorthy, Rajesh Kumar Dhanaraj, C N Vanitha, Md Shohel Sayeed

“…Results demonstrate that the proposed model achieved a 1.86% increase in throughput, a 2.56% reduction in delay, and a 3.18% improvement in energy efficiency when compared to existing schemes such as PSO, ALO, and SA-AOA.…”
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Research on Flexible Job Shop Scheduling Method for Agricultural Equipment Considering Multi-Resource Constraints by Zhangliang Wei, Zipeng Yu, Renzhong Niu, Qilong Zhao, Zhigang Li

“…To tackle this complex problem, a Multi-Objective Discrete Grey Wolf Optimization (MODGWO) algorithm is proposed. The MODGWO algorithm integrates a hybrid initialization strategy and a multi-neighborhood local search to effectively balance the exploration and exploitation capabilities. …”
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Wide area cooperative resource allocation algorithm for shortwave communication access network by Guojun LI, Xu HOU, Changrong YE, Yiping LUO

“…Aiming at the problem that short-wave point-to-point communication was not reliable enough to meet the actual needs, a wide area cooperative resource allocation algorithm based on shortwave communication access network was proposed.The reliability of the shortwave communication was improved by invoking multiple stations to coordinately guarantee users from different channels.The resource allocation problem was decomposed into two sub-problems of channel and station matching and station allocation.Firstly, the maximum expected success rate matching model was established to match the channel and the station, and the stations allocated to the channel were combined into different guarantee schemes.Then, the fuzzy analytic hierarchy process and the entropy weight method were used to obtain the subjective and objective scores of the scheme, and the optimal scheme was selected through fusion of evidence reasoning.The results show that the proposed algorithm can effectively improve the success rate of shortwave communication and has good adaptability.…”
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