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…”
Get full text

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.…”
Get full text

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. …”
Get full text

Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

Get full text

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. …”
Get full text

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. …”
Get full text

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.…”
Get full text

Application of adaptive artificial bee colony algorithm in environmental and economic dispatching management by Zhang Longyue, Zhang Haoyan

“…With the increasingly serious global environmental and energy issues, more countries are using environmental and economic dispatch (EED) models to optimize power systems. To better optimize the power system, an adaptive artificial bee colony (ABC) algorithm based on memory feedback mechanism was put forward to address the EED model, and the adaptive algorithm was used to adaptively adjust the population size. …”
Get full text

Theoretical and Experimental Study of Energy-Harvesting and Movement-Sensing Solutions in Pneumatic Systems by Monica Tiboni, Federico Scassola, Alessandro Zanacchi, Marco Ghidini

“…Following confirmation of the adapted model’s validity, the authors propose using genetic algorithms to design an optimized mechanical energy harvester. …”
Get full text

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. …”
Get full text

A machine learning algorithm for personalized healthy and sustainable grocery product recommendations by Laura Z.H. Jansen, Kwabena E. Bennin

Get full text

Comparison of methods for tuning machine learning model hyper-parameters: with application to predicting high-need high-cost health care users by Christopher Meaney, Xuesong Wang, Jun Guan, Therese A. Stukel

“…Hyper-parameter tuning using any HPO algorithm/sampler improved model discrimination (AUC=0.84), resulted in models with near perfect calibration, and consistently identified features predictive of high-need high-cost health care users. …”
Get full text

Performance of quantum approximate optimization with quantum error detection by Zichang He, David Amaro, Ruslan Shaydulin, Marco Pistoia

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising candidate for scaling up to tackle real-world applications. …”
Get full text

ICSO: A Novel Hybrid Evolutionary Approach with Crisscross and Perturbation Mechanisms for Optimizing Generative Adversarial Network Latent Space by Zhihui Chen, Ting Lan, Zhanchuan Cai, Zonglin Liu, Renzhang Chen

“…This paper proposes a novel improved crisscross optimization (ICSO) algorithm, a hybrid evolutionary approach that integrates crisscross optimization and perturbation mechanisms to find the suitable latent vector. …”
Get full text

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.…”
Get full text

Optimization of emission scheduling in microgrids with electric vehicle integration by Peng Cao, Daowang Wang, Xingyang Jiang

“…Then, aiming to minimize both the operational cost and pollution emission treatment cost of the microgrid, an emission dispatch optimization model was developed. The whale optimization algorithm (WOA) was chosen as the solving algorithm, and an improved WOA (IWOA) was obtained by optimizing the original WOA in terms of population initialization and position updating parameters. …”
Get full text

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. …”
Get full text

A Hybrid EV Charging Approach Based on MILP and a Genetic Algorithm by Syed Abdullah Al Nahid, Junjian Qi

“…The proposed method includes (1) a centralized day-ahead optimal scheduling mechanism and EV shifting process based on mixed-integer linear programming (MILP) and (2) a distributed control strategy based on a genetic algorithm (GA) that dynamically adjusts the charging rate in real-time grid scenarios. …”
Get full text

CP-YOLO: An Algorithm for Cigarette Pack Defects Detection Based on CCD Images by Peng Dong, Weihua Feng, Rui Wang, Mingyan Zhang, Qunye Hong, Yongsheng Wang, Di Wang, Guohao Zong

“…Consequently, this paper proposes an improved CP-YOLO algorithm based on YOLOv5 to address the characteristics of cigarette pack defects including large size variations and complex foreground-background information. …”
Get full text

Toward an algorithm of percutaneous microelectrolysis: a randomized clinical trial on invasive techniques by Carlos Eduardo Girasol, Nathaly Escobar Durán, Santiago Marcelo D’Almeida, Oscar Ariel Ronzio

“…CONCLUSIONS: All needling techniques demonstrated analgesic effects on myofascial trigger points, with the algorithm-enhanced MEP showing the most notable improvement in self-reported pain. …”
Get full text