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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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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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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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Electroreduction of hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a back propagation neural network
Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI), but shortcomings are tedious preparation and short...
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Cadmium toxicity to and accumulation in a soil collembolan (Folsomia candida): major factors and prediction using a back-propagation neural network model
Accurate prediction of cadmium (Cd) ecotoxicity to and accumulation in soil biota is important in soil health. However, very limited information on...
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Simulation analysis of carbon peak path in China from a multi-scenario perspective: evidence from random forest and back propagation neural network models
China faces tough challenges in the process of low-carbon transformation. To determine whether China can achieve its new 2030 carbon peaking and...
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Intelligent prediction of rockburst in tunnels based on back propagation neural network integrated beetle antennae search algorithm
Rockburst is one of the major engineering geological disasters of underground engineering. Accurate rockburst intensity level prediction is vital for...
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Grade evaluation of black-odorous urban rivers in the Greater Bay Area of China using an improved back propagation (BP) neural network
With the rapid development of urbanization, the urban water environment is receiving continuous attention. It is necessary to understand water...
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Multi-step wind speed forecasting based on a hybrid decomposition technique and an improved back-propagation neural network
Accurate wind speed forecasting (WSF) not only ensures stable power system operation but also contributes to enhancing the competitiveness of wind...
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Assessing the risk of green building materials certification using the back-propagation neural network
The development and implementation of green product certification have created new requirements for risk assessment of the certification process....
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Online Detection of Component Concentration in Synthetic Sodium Aluminate Solution Using Orthogonal Regression and BP Neural Network
The online measurement of component concentrations in sodium aluminate solution is crucial for the Bayer alumina production process. In this paper,...
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Prediction NOx emission from sintering plant with a radial basis function and back propagation hybrid neural network
NO x emission in iron and steel enterprises mainly comes from sintering flue gas. Traditional artificial neural networks cannot meet the requirements...
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Back-propagation neural network: Box–Behnken design modelling for optimization of copper adsorption on orange zest biochar
Heavy metals adsorption by adsorbents prepared from natural materials is a low-cost effective method for their removal from aqueous environments....
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Simulation of the Nitrate Concentrations in Consumed Well Water Using the Error Gradient Backpropagation Neural Network: A Case Study: M’bahiakro (Central-Eastern Ivory Coast)
In M’bahiakro, nitrate contamination of drinking well water is becoming a cause for concern and continues despite the efforts made in the town. To...
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Independent parallel pyrolysis kinetics of model components in sewage sludge analyzed by BPM neural network
Analyzing the kinetic behavior of sewage sludge pyrolysis is essential for the design of efficient reactors to produce biofuel and syngas. To...
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Using Genetic Algorithm and Particle Swarm Optimization BP Neural Network Algorithm to Improve Marine Oil Spill Prediction
Numerical oil spill models, which predict the transport and behavior of oil spills, are an essential tool for risk assessment and clean-up during an...
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Joint probability distribution of weather factors: a neural network approach for environmental science
This study introduces methodologies for constructing joint probability distribution functions utilizing the Copula function and neural networks, and...
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Slide type landslide susceptibility assessment of the Büyük Menderes watershed using artificial neural network method
The Büyük Menderes watershed is the largest drainage watershed in Western Anatolia with an area of approximately 26,000 km 2 . In the study area,...
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Mg-Fe-LDH for Aquatic Selenium Treatment: Adsorption, RSM Modeling, and Machine Learning Neural Network
Different aqueous selenium species including selenite, selenate, and selenocyanate, can be harmful to both humans and other life forms. Considering...
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Modeling and Analysis of Copper, Iron, and Cobalt Recovery in a Hybrid Sulfuric Acid–Sodium Chloride Media Using Artificial Neural Network
The effects of operating conditions on copper, iron, and cobalt dissolution from sulfide ores in sulfuric acid–sodium chloride media are predicted...
