Improved Nonprobabilistic Global Optimal Solution Method and Its Application in Bridge Reliability Assessment by Xiaoya Bian, Xuyong Chen, Hongyin Yang, Chen You

“…Utilizing the improved one-dimensional optimization algorithm conveniently solved the nonprobabilistic reliability index, however, only searching the part of probable failure points. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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RESEARCH ON THE REMAINING INTENSITY OF PIPELINE CORROSION BASED ON IWOA-LSSVM by ZHANG Jia, Ll LinFeng, WANG HaoJie, ZHANG Ting

“…In response to pipeline corrosion surplus intensity, a surplus intensity prediction method based on the Improved Whale Optimization Algorithm (IWOA ) -Least Square Support Vector Machine (LSSVM) combination algorithm model. …”
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Improved Estimation Procedure of Cage-Induction-Motor-Equivalent Circuit Parameters Based on Two-Stage PSO Algorithm by Jovan Vukašinović, Saša Štatkić, Nebojša Arsić, Nebojša Mitrović, Bojan Perović, Andrijana Jovanović

“…This paper analyzes errors in the estimation of induction-motor-equivalent circuit parameters using an improved combined two-stage Particle Swarm Optimization (PSO) method. …”
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Improved Electrochemical–Mechanical Parameter Estimation Technique for Lithium-Ion Battery Models by Salvatore Scalzo, Davide Clerici, Francesca Pistorio, Aurelio Somà

“…An error analysis—based on the Root Mean Square Error (RMSE) and confidence ellipses—confirms that the inclusion of mechanical measurements significantly improves the accuracy of the identified parameters and the reliability of the algorithm compared to approaches relying just on electrochemical data. …”
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Combining the Improved RGB Water-Filling Algorithm With Penumbra Removal Technique for Shadow Removal From Digitized Images by You-Chang Liu, Cheng-Ta Chuang

“…The proposed method introduces an RGB water-filling algorithm specifically designed to address soft shadows, optimized with matrix operations and a streamlined processing workflow that substantially enhance the computational efficiency over existing methods. …”
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Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

“…Accurate prediction can help passengers make travel plans and improve travel efficiency. Given the nonlinearity, randomness, and complexity of bus arrival time, this paper proposes the use of a wavelet neural network (WNN) model with an improved particle swarm optimization algorithm (IPSO) that replaces the gradient descent method. …”
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Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

“…To address this problem, the velocity update equation of the original PSO algorithm is modified by incorporating a dynamic linear decreasing inertia weight, which improves the PSO algorithm’s convergence behaviour and aids both local and global search. …”
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Multi-strategy improved runge kutta optimizer and its promise to estimate the model parameters of solar photovoltaic modules by Serdar Ekinci, Rizk M. Rizk-Allah, Davut Izci, Emre Çelik

“…In our endeavor, we introduce a multi-strategy improvement approach for the Runge Kutta (RUN) optimizer, a cutting-edge tool used for tackling this critical task in both single-diode and double-diode PV unit models. …”
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Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

“…The goals of this study were to (i) identify optimal spectral indices and texture features from RGB and multispectral (MS) images and (ii) improve the accuracy of PNC prediction by combining optimal features with ML. …”
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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Additionally, the SPM chaotic mapping strategy is utilized for population initialization, while the introduction of the golden sine operator variation strategy enhances the local search capabilities of the algorithm. The adaptive swoop switching strategy adjusts the search intensity, thereby improving the global search performance and convergence speed of the Arctic Puffin Optimization (APO). …”
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Predicting excavation-induced lateral displacement using improved particle swarm optimization and extreme learning machine with sparse measurements by Cheng Chen, Guan-Nian Chen, Song Feng, Xiao-Zhen Fan, Liang-Tong Zhan, Yun-Min Chen

“…This study presents a novel prediction method using an extreme learning machine (ELM) optimized by an improved particle swarm optimization (IPSO) algorithm. …”
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Comprehensive recognition algorithm of RS code based on fast code root trial by Xiaolin ZHANG, Xiuqiao LI, Rongchen SUN

“…In order to solve the problem of high computation and high missed alarm probability of RS (Reed-Solomon) codes for recognition, comprehensive recognition algorithm of RS codes based on fast code root trial was proposed.Firstly, the check relationship was solved in binary equivalently and fast code root trial was used to check parameters in sequence.Secondly, according to distribution characteristics of the combined code roots, m-level primitive polynomial field and error correction ability was associatively determined.Finally, the short codes and long codes were given different confidence weights and the determined parameters were comprehensively analyzed.The optimal parameter was selected and the generate polynomial was calculated.The proposed algorithm did not need prior information such as signal-to-noise ratio (SNR), and had good adaptability.The simulation results show that the proposed algorithm can effectively reduce the missed alarm probability under the condition of low complexity.Compared with the conventional hard decision algorithm, the performance of the proposed algorithm is improved, and the parameter recognition of RS codes can be completed quickly.…”
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ＲGB-DSLAM Visual Odometry Optimization Algorithm by DONG Jing-wei, JIANG Yi-ming, HAN Zhi-yu

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Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

“…To address this issue, this paper proposes a novel prediction model based on the Improved Sparrow Search Algorithm-optimized XGBoost (ISSA-XGBoost). …”
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An Innovative Indoor Localization Method for Agricultural Robots Based on the NLOS Base Station Identification and IBKA-BP Integration by Jingjing Yang, Lihong Wan, Junbing Qian, Zonglun Li, Zhijie Mao, Xueming Zhang, Junjie Lei

“…Next, the collected received signal strength indication (RSSI) data are processed using Kalman filtering and Min-Max normalization, suppressing signal fluctuations and accelerating the gradient descent convergence of the distance measurement model. Finally, the improved black kite algorithm (IBKA) is enhanced with tent chaotic mapping, a lens imaging reverse learning strategy, and the golden sine strategy to optimize the weights and biases of the BP neural network, developing an RSSI-based ranging algorithm using the IBKA-BP neural network. …”
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Research on the Gas Emission Quantity Prediction Model of Improved Artificial Bee Colony Algorithm and Weighted Least Squares Support Vector Machine (IABC-WLSSVM) by Lei Wang, Jinghang Li, Wenbo Zhang, Yu Li

“…At the same time, the improved artificial bee colony algorithm is used to optimize the kernel width σ and regularization parameter λ of WLSSVM, which improves the prediction accuracy and convergence rate of WLSSVM. …”
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