Search
Search Results
-
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...
-
Back propagation model for prediction of deposition parameters in plasma sprayed WC-based coatings
The deposition parameters frequently have a significant impact on the characteristics of plasma spray coating. Due to the intricate chemical and...
-
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...
-
Back-propagation optimization and multi-valued artificial neural networks for highly vivid structural color filter metasurfaces
We introduce a novel technique for designing color filter metasurfaces using a data-driven approach based on deep learning. Our innovative approach...
-
Impact damage prediction of CFRP laminates with rubber protective layer using back-propagation neural networks
The carbon fiber–reinforced polymer (CFRP) structure in the aviation industry is typically subject to low-velocity impact damage during the assembly...
-
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)...
-
Back-propagation extreme learning machine
Incremental Extreme Learning Machine (I-ELM) is a typical constructive feed-forward neural network with random hidden nodes, which can automatically...
-
Resilient back-propagation machine learning-based classification on fundus images for retinal microaneurysm detection
BackgroundThe timely diagnosis of medical conditions, particularly diabetic retinopathy, relies on the identification of retinal microaneurysms....
-
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...
-
Deciphering Soil Fertility of Tobacco Planting Fields with Back Propagation Artificial Neural Networks in Southwest China
Assessing soil quality via the integrated soil fertility index (IFI) is essential for enhancing soil sustainability. In this context, the emergent...
-
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...
-
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...
-
A new comprehensive model of thermal conductivity for hydrofluoroolefins refrigerants using feed-forward back-propagation neural networks
In this work, the thermal conductivity of refrigerants systems from three different hydrofluoroolefins including R1234yf, R1234ze(E), and R1233zd(E)...
-
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...
-
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...
-
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...
-
Thermal Error Modeling of Numerical Control Machine Based on Beetle Antennae Search Back-propagation Neural Networks
Thermal errors are one key impact factor on the processing accuracy of numerical control machine. This study targeted at a certain vertical...
-
Multi-output incremental back-propagation
Deep learning techniques can form generalized models that can solve any problem that is not solvable by traditional approaches. It explains the...
-
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...
-
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...
