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Multi-back-propagation Algorithm for Signal Neural Network Decomposition
In this paper, a novel back-propagation error technique is presented. This neural network structure allows for two fundamental basic modes: (1) To...
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Memristive crossbar-based circuit design of back-propagation neural network with synchronous memristance adjustment
The performance improvement of CMOS computer fails to meet the enormous data processing requirement of artificial intelligence progressively. The...
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Shallow water bathymetry based on a back propagation neural network and ensemble learning using multispectral satellite imagery
The back propagation (BP) neural network method is widely used in bathymetry based on multispectral satellite imagery. However, the classical BP...
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Construction and optimization of non-parametric analysis model for meter coefficients via back propagation neural network
This study addresses the drawbacks of traditional methods used in meter coefficient analysis, which are low accuracy and long processing time. A new...
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Estimating maize evapotranspiration based on hybrid back-propagation neural network models and meteorological, soil, and crop data
Crop evapotranspiration is a key parameter influencing water-saving irrigation and water resources management of agriculture. However, current models...
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Corrosion fatigue life prediction method of aluminum alloys based on back-propagation neural network optimized by Improved Grey Wolf optimization algorithm
In order to improve the accuracy of the corrosion fatigue life prediction model for the 7050 aluminum alloy, this study presents a corrosion fatigue...
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Back propagation artificial neural network for diagnose of the heart disease
Nowadays, coronary heart disease is one of the most fatal disease globally. Many researchers and medical technicians have developed and designed...
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An intelligent model to decode students’ behavioral states in physical education using back propagation neural network and Hidden Markov Model
This paper highlights the need for intelligent analysis of students’ behavioral states in physical education tasks. The hand-ring inertial data is...
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Interpretable Back Propagation Neural Network Based Fast Directional Modulation Design
Traditional solutions for directional modulation (DM) rely on weight optimization methods, which has high computational complexity and cannot be...
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Quantitative Evaluation of NDE Reliability Based on Back Propagation Neural Network and Fuzzy Comprehensive Evaluation
There are some problems in the quality evaluation of network distance education, such as the large error in the quantitative results of the...
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Predictive model of surface roughness in milling of 7075Al based on chatter stability analysis and back propagation neural network
Accurate prediction of the machining quality such as the surface roughness is one of the main objectives of the intelligent manufacturing research....
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Multi-Objective Optimization for Turning Process of 304 Stainless Steel Based on Dung Beetle Optimizer-Back Propagation Neural Network and Improved Particle Swarm Optimization
Austenite stainless steel of type 304 is one of the most difficult materials to process. During the machining process, parts easily generate higher...
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Mind evolutionary algorithm optimization in the prediction of satellite clock bias using the back propagation neural network
Satellite clock bias is the key factor affecting the accuracy of the single point positioning of a global navigation satellite system. The...
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Finite element model simulation and back propagation neural network modeling of void closure for an extra-thick plate during gradient temperature rolling
The void closure behavior in a central extra-thick plate during the gradient temperature rolling was simulated and a back propagation (BP) neural...
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Optimal design of groundwater pollution monitoring network based on a back-propagation neural network surrogate model and grey wolf optimizer algorithm under uncertainty
In the optimal design of groundwater pollution monitoring network (GPMN), the uncertainty of the simulation model always affects the reliability of...
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Application of Northern Goshawk Back-Propagation Artificial Neural Network in the Prediction of Monohydroxycarbazepine Concentration in Patients with Epilepsy
IntroductionA northern goshawk back-propagation artificial neural network (NGO-BPANN) model was established to predict monohydroxycarbazepine (MHD)...
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An improved genetic-back propagation network constructing strategy for high-precision state-of-charge estimation of complex-current-temperature-variation lithium-ion batteries
Environmental issues have driven the booming development of lithium-ion battery technology, and improving the accuracy of state-of-charge (SOC)...
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Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China
This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess...
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Pipeline damage identification based on an optimized back-propagation neural network improved by whale optimization algorithm
With the advantages of high economy and large transportation capacity, pipeline transportation is commonly used in industrial production. Pipeline...
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A method of forecasting trade export volume based on back-propagation neural network
Financial forecasting has been greatly improved in recent years, but at long horizons, forecast accuracy may be low. Foreign trade plays an important...
