Suchergebnisse - "intelligent optimization algorithm"

A stacking-based ensemble learning method for earthquake casualty prediction von Cui, Shaoze, Yin, Yunqiang, Wang, Dujuan, Li, Zhiwu, Wang, Yanzhang

“… The estimation of the loss and prediction of the casualties in earthquake-stricken areas are vital for making rapid and accurate decisions during rescue …”
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A critical review on intelligent optimization algorithms and surrogate models for conventional and unconventional reservoir production optimization von Wang, Lian, Yao, Yuedong, Luo, Xiaodong, Daniel Adenutsi, Caspar, Zhao, Guoxiang, Lai, Fengpeng

“… •This review study aims to help promote research activities within the field of reservoir production optimization.•A variety of intelligent optimization …”
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Prediction and design of high hardness high entropy alloy through machine learning von Ren, Wei, Zhang, Yi-Fan, Wang, Wei-Li, Ding, Shu-Jian, Li, Nan

“… [Display omitted] •Particle swarm algorithm is used to inversely optimize the alloy composition according to target performance.•An optimized feature set …”
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Real-time monitoring of the corrosion behaviour of the 304SS in HCl solution using BPNN with joint image recognition and electrochemical noise von Zhang, Haofeng, Wu, Zhiqin, Chen, Yang, Feng, Kaixuan, Yan, Hong, Song, Honggun, Luo, Chao, Hu, Zhi

“… Electrochemical noise has an important reference role in the study of early corrosion; however, a direct correlation between the microscopic morphology and the …”
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Self-optimization wavelet-learning method for predicting nonlinear thermal conductivity of highly heterogeneous materials with randomly hierarchical configurations von Linghu, Jiale, Dong, Hao, Gao, Weifeng, Nie, Yufeng

“… In the present work, we propose a self-optimization wavelet-learning method (SO-W-LM) with high accuracy and efficiency to compute the equivalent nonlinear …”
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A survey of welding robot intelligent path optimization von Wang, Xuewu, Zhou, Xin, Xia, Zelong, Gu, Xingsheng

“… Welding robots are widely used for most welding works in manufacturing industries due to their flexible, efficient and accurate operation. At the same time, it …”
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Framework for multivariate carbon price forecasting: A novel hybrid model von Zhang, Xuankai, Zong, Ying, Du, Pei, Wang, Shubin, Wang, Jianzhou

“… The complex characteristics of volatility and non-linearity of carbon price pose a serious challenge to accurately predict carbon price. Therefore, this study …”
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A combined prediction model based on secondary decomposition and intelligence optimization for carbon emission von Yang, Hong, Wang, Maozhu, Li, Guohui

“… •An improved singular spectrum decomposition is proposed.•High complexity components are secondarily decomposed to reduce its complexity.•An improved …”
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A novel deep learning framework for landslide susceptibility assessment using improved deep belief networks with the intelligent optimization algorithm von Meng, Shaoqiang, Shi, Zhenming, Li, Gang, Peng, Ming, Liu, Liu, Zheng, Hongchao, Zhou, Changshi

“… This research proposed a novel deep learning framework that combines the Laplace function sparse regularized continuous deep belief network (LSCDBN) and the …”
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Ship route planning based on intelligent mapping swarm optimization von Ma, Weihao, Han, Yueyi, Tang, Huan, Ma, Dongfang, Zheng, Huarong, Zhang, Yang

“… •A new strategy for simultaneously optimizing ship route and speed is proposed.•Carbon tax policy and weather information are considered.•A two-layer mapping …”
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A novel variable selection method based on combined moving window and intelligent optimization algorithm for variable selection in chemical modeling von Zhang, Pengfei, Xu, Zhuopin, Wang, Qi, Fan, Shuang, Cheng, Weimin, Wang, Haiping, Wu, Yuejin

“… We propose a new wavelength selection algorithm based on combined moving window (CMW) and variable dimension particle swarm optimization (VDPSO) algorithm. CMW …”
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Structural damage detection based on cross-correlation function with data fusion of various dynamic measurements von Wang, Xiaojuan, Chen, Feng, Zhou, Hongyuan, Ni, Pinghe, Wang, Lihui, Zhang, Jian

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A novel interpretable wind speed forecasting based on the multivariate variational mode decomposition and temporal fusion transformer von Xu, Rui, Fang, Haoyu, Zeng, Huanze, Wu, Binrong

“… Accurate and efficient wind speed forecasting is essential for the stable operation of wind farm and power grids. However, the high volatility of wind speed, …”
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Forecasting carbon price in China using a novel hybrid model based on secondary decomposition, multi-complexity and error correction von Yang, Hong, Yang, Xiaodie, Li, Guohui

“… As global warming intensifies, the reduction of carbon emissions is imminent. Carbon price is directly related to whether carbon can be effectively reduced …”
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Intelligent Optimization Algorithm for Digital Media Art CAD Design Combining Media Big Data von Zhan, Ning, Mei, Pozhang

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Moving regression artificial neural network framework for reliability evaluation of complex structure/system von Lu, Peng, Chen, Yong-Jing, Dong, Rui-Yi

“… For evaluating reliability level of complex structure/system, a moving regression artificial neural network (MRANN) framework is proposed based on artificial …”
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Migration-based algorithm library enrichment for constrained multi-objective optimization and applications in algorithm selection von Wang, Yan, Zuo, Mingcheng, Gong, Dunwei

“… It is of necessity to select appropriate optimization algorithms from an algorithm library due to the universality of constrained multi-objective optimization …”
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A multi-objective ensemble learning model with re-decomposition and residual learning for grain futures price prediction von Zhang, Li, Sun, Weixin, Abedin, Mohammad Zoynul, Wang, Yong

“… Food security is crucial for social stability, and accurate price fluctuation predictions are essential for policy-making, business operations, and investment …”
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A multi-stage forecasting system for daily ocean tidal energy based on secondary decomposition, optimized gate recurrent unit and error correction von Yang, Hong, Wu, Qingsong, Li, Guohui

“… Tidal energy, as a new energy, has very high research potential and practical application value. For the characteristics of tidal energy such as …”
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A Spectral Convolutional Neural Network Model Based on Adaptive Fick’s Law for Hyperspectral Image Classification von Wu, Tsu-Yang, Li, Haonan, Kumari, Saru, Chen, Chien-Ming

“… Hyperspectral image classification stands as a pivotal task within the field of remote sensing, yet achieving high-precision classification remains a …”
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