A recommender algorithm based on SVD ++model under trust network by Peiwu CHEN, Fangxing SHU

“…Recommender algorithms are usually modeled based on user behavior data.However, the sparseness of explicit behavior data may cause the cold start problem of recommender algorithms.In order to solve the impact of data sparseness and cold-start problems on the effect of recommender algorithms, implicit trust relationship based on user similarity was introduced based on the existing revealed trust relationship, and a new recommender algorithm was designed through the SVD++ implicit semantic model.In order to improve the effect of the algorithm, the neighborhood model was integrated further, and the algorithm score prediction formula and loss function were derived.In the Epinions open source data set, RMSE and MAE were used as test indicators, and comparative experiments were conducted on the entire user set and the cold start user set.The experimental results show that the recommender algorithm can optimize the cold start problem of the original recommender algorithm to a certain extent, and achieve a better rating prediction accuracy.…”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

“…Methods We developed a novel hybrid model integrating convolutional neural network (CNN), Transformer, and Whale Optimization Algorithm (WOA) for arrhythmia prediction in AMI patients. …”
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An analytical optimal calibration framework of bonded particle model for rock strength envelop modelling by Xiaoxiong Zhou, Hongyi Xu, Qiuming Gong, Yanan Ma, Weiqiang Xie

“…Adaptive moment estimation (Adam) was chosen as the iterative optimization algorithm to avoid the vanishing gradient problem. …”
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Study on the Switching Model Predictive Control Algorithm in Batch Polymerization Process by Jong Nam Kim, Chun Bae Ma, Hyok Jo, Un Chol Han, Hyon-Tae Pak, Son Il Hong, Ri Myong Kim

“…Finally, a switching model predictive control algorithm that determines the optimal manipulated value based on the on-line updated step response model is constructed, and a cascade control system using this algorithm is introduced to the temperature control of batch polyvinyl chloride suspension polymerization process. …”
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Applicability of Different Assimilation Algorithms in Crop Growth Model Simulation of Evapotranspiration by Jingshu Wang, Ping Li, Rutian Bi, Lishuai Xu, Peng He, Yingjie Zhao, Xuran Li

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A Wi-Fi RSS-RTT Indoor Positioning Model Based on Dynamic Model Switching Algorithm by Xu Feng, Khuong An Nguyen, Zhiyuan Luo

“…To address this challenge, we propose an algorithm that dynamically selects the most optimal Wi-Fi positioning model for each location. …”
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Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…For the Sinkhole attack problem of wireless sensor network（WSN），a detection algorithm based on fusion of ant colony optimization（ACO）and P2P trust model was proposed.Firstly，ant colony optimization algorithm was used to detect the existence of a Sinkhole attack in route and generate the alarm information of sensor nodes. …”
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Sinkhole attack detection based on fusion of ACO and P2P trust model in WSN by Wumaier HENIGULI

“…For the Sinkhole attack problem of wireless sensor network（WSN），a detection algorithm based on fusion of ant colony optimization（ACO）and P2P trust model was proposed.Firstly，ant colony optimization algorithm was used to detect the existence of a Sinkhole attack in route and generate the alarm information of sensor nodes. …”
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Inverse methods and integral-differential model demonstration for optimal mechanical operation of power plants – numerical graphical optimization for second generation of tribology... by Casesnoves Francisco

“…Stepping forward from a previous conference contribution, the article focuses on extension of inverse problem algorithms to integral-differential modelling and formal/strict demonstration of graphical-optimization method. …”
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Enhanced Prediction of California Bearing Ratio (CBR) Values in Geotechnical Engineering Using Decision Tree Algorithm and Meta-Heuristic Optimizations by Linda Davies, Dominik Jánošík

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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…By selecting different features, the optimal feature combination for predicting rock compressive strength was obtained, and the optimal parameters for different models were obtained through the Sparrow Search Algorithm (SSA). …”
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The Elitist Non-Dominated Sorting Crisscross Algorithm (Elitist NSCA): Crisscross-Based Multi-Objective Neural Architecture Search by Zhihui Chen, Ting Lan, Dan He, Zhanchuan Cai

“…This paper proposes a multi-objective evolutionary algorithm called the elitist non-dominated sorting crisscross algorithm (elitist NSCA) and applies it to neural architecture search, which considers two optimization objectives: the accuracy and network parameters. …”
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Study on the anti-penetration randomness of metal protective structures based on optimized artificial neural network by Lan Liu, Weidong Chen, Shengzhuo Lu, Yanchun Yu, Mingwu Sun

“…And by adopting the Back Propagation Neural Network optimized by Dynamic Lifecycle Genetic Algorithm (DLGABPNN) as the surrogate model of APRMPS, this paper presents the technical route of DLGABPNN-MCS, the Monte Carlo Simulation with DLGABPNN calculation as repeated sampling tests, to addressing APRMPS. …”
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A rapid detection method for egg quality using CARS and SSA⁃XGBoost improved by combining hyperspectral analysis by WANG Linyi, ZOU Qianying, SUN Qiang

“…Optimizing multiple hyperparameters of the XGBoost model through the Tartary Sea Salp Swarm Algorithm to improve the predictive performance of the XGBoost model. …”
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Gaussian Process Regression Total Nitrogen Prediction Based on Data Decomposition Technology and Several Intelligent Algorithms by WANG Yongshun, CUI Dongwen

“…Total nitrogen (TN) is one of the important indicators to reflect the degree of water pollution and measure the eutrophication status of lakes and reservoirs.To improve the accuracy of TN prediction,based on the empirical wavelet transform (EWT) and wavelet packet transform (WPT) decomposition technology,this paper proposes a Gaussian process regression (GPR) prediction model optimized by osprey optimization algorithm (OOA),rime optimization algorithm (ROA),bald eagle search (BES) and black widow optimization algorithm (BWOA) respectively.Firstly,the TN time series is decomposed into several more regular subsequence components by EWT and WPT respectively.Then,the paper briefly introduces the principles of OOA,ROA,BES,and BWOA algorithms and applies OOA,ROA,BES,and BWOA to optimize GPR hyperparameters.Finally,EWT-OOA-GPR,EWT-ROA-GPR,EWT-BES-GPR,EWT-BWOA-GPR,WPT-OOA-GPR,WPT-ROA-GPR,WPT-BES-GPR,WPT-BWOA-GPR models (EWT-OOA-GPR and other eight models for short) are established to predict the components of TN by the optimized super-parameters.The final prediction results are obtained after reconstruction,and WT-OOA-GPR,WT-ROA-GPR,WT-BES-GPR and WT-BWOA-GPR models based on wavelet transform (WT) are built.Eight models,including EWT-OOA-SVM based on support vector machine (SVM),the paper compares the unoptimized EWT-GPR,WPT-GPR models,and the uncomposed OOA-GPR,ROA-GPR,BES-GPR,and BWOA-GPR models.The models were verified by the monitoring TN concentration time series data of Mudihe Reservoir,an important drinking water source in China,from 2008 to 2022.The results are as follows.① The average absolute percentage error of eight models such as EWT-OOA-GPR for TN prediction is between 0.161% and 0.219%,and the coefficient of determination is 0.999 9,which is superior to other comparison models,with higher prediction accuracy and better generalization ability.② EWT takes into account the advantages of WT and EMD.WPT can decompose low-frequency and high-frequency signals at the same time.Both of them can decompose TN time series data into more regular modal components,significantly improving the accuracy of model prediction,and the decomposition effect is better than that of the WT method.③ OOA,ROA,BES,and BWOA can effectively optimize GPR hyperparameters and improve GPR prediction performance.…”
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Optimization method of investment package based on Markowitz portfolio theory by A. D. Baydalin

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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines by Lelisa Wogi, Amruth Thelkar, Tesfabirhan Shoga Tahiro, Tadele Ayana, Shabana Urooj, Samia Larguech

“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
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Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

“…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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Prediction of Spatiotemporal Distribution of Electric Vehicle Charging Load Based on Multi-Source Information by WANG Qiang, BI Yuhao, GAO Chao, SONG Duoyang

“…Additionally， the Dijkstra algorithm is improved to plan charging paths more effectively by including real-time road condition data. …”
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Nearest-Better Clustering-Based Memetic Algorithm for Berth Allocation and Crane Assignment Problem by Jiawei Wu

“…In this paper, we investigate the capability of differential evolution (DE) algorithms in solving BACAP by modeling berth allocation as a continuous optimization problem. …”
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