Optimization of Aluminum Alloy Rifled Barrel ECM Process Parameters Based on GA-BP Algorithm

Zheng, Yaze; Tang, Lin; Liu, Shiying; Zhou, Jiakai

doi:10.1088/1742-6596/2383/1/012131

Cited by 2 publications

(2 citation statements)

References 4 publications

(2 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It indicates the proposed DBN‐BRO model learned well from the given experimental data and fit for the prediction process. Besides, Zheng et al [ 57 ] stated that more than 0.9 regression coefficient could be reasonable for a valid prediction model because such models can possess linear correlation between input and target vectors at a very high rate. Thus the proposed model is valid and suitable for ECDM process prediction.…”

Section: Resultsmentioning

confidence: 99%

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

2023

View full text Add to dashboard Cite

Alumina‐Zirconium dioxide (Al2O3‐ZrO2) Ceramic Composite Material (CCM) is specifically known for its enhanced mechanical and corrosion resistance properties and is widely used as raw material for mechanical parts like, pump components, die inserts, bearings, etc. As a result, industrialists are searching for an efficient method for machining this Al2O3‐ZrO2 material. In this regard, a hybrid unconventional machining process called Electrochemical Discharge Machining (ECDM) is adapted to analyze the machinability of Al2O3‐ZrO2 CCM. Besides, to ensure the efficiency of the ECDM process, a magnetic field is also given to the tool electrode during this study to improve the Material Removal Rate (MRR) of the ECDM machine. The experiment is designed using Response Surface Methodology (RSM) by changing the magnitudes of input controls, namely Electrolytic Concentration (EC), Inter‐electrode Gap (IEG) and Applied Voltage (AV). Moreover, a novel hybrid machine learning optimization strategy called Deep Belief Network based Battle Royal Optimization (DBN‐BRO) algorithm is developed to predict and optimize the ECDM process. Finally, the optimum results are perceived from 55 V AV, 22.727% EC and 40.909 mm IEG input levels. The proposed method shows less than 0.6207 Root Mean Square Error (RMSE) and tools nearly 80 iterations for optimizing the results.

show abstract

Section: Resultsmentioning

confidence: 99%

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

2023

View full text Add to dashboard Cite

show abstract

“…It is currently the most widely used and the most intuitively structured neural network with the easiest-to-understand working principle. It is highly flexible and has strong data fitting ability, and can learn and store a large number of input-output pattern mappings [4]. During the training process, the neural network continuously adjusts the weights and thresholds between the input layer and the hidden layer, and between the hidden layer and the output layer.…”

Section: Bp Neural Networkmentioning

confidence: 99%

Research on Price Forecast Based on Genetic Algorithm Optimizing Neural Network

Zou,

Zheng

2023

BCPBM

View full text Add to dashboard Cite

This paper chooses a number of indicators such as per capita GDP and economic level. First of all, the box diagram method is used to remove the outliers in the data, and then the Box-Cox transform is used to normalize the data. Then calculate the correlation coefficient between features, and finally determine 15 features for the construction of the model. On the basis of BP neural network, using GA algorithm to optimize the weight setting, a GA-BP model is established to predict the prices of different types of forecasting objects. Combined with the search ability of genetic algorithm optimization algorithm and the learning ability of BP neural network, the advantages of both are fully utilized to get better regression prediction results. The result of GA-BP is better than that of BP neural network, which shows that the prediction accuracy of the model is very high, in order to provide some reference for the prediction of other fields.

show abstract

Optimization of Aluminum Alloy Rifled Barrel ECM Process Parameters Based on GA-BP Algorithm

Cited by 2 publications

References 4 publications

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

Multi‐Objective Optimization During Magnetic Field Assisted ECDM of Alumina‐Zirconium Dioxide Ceramic Composite using Battle Royale Optimization

Research on Price Forecast Based on Genetic Algorithm Optimizing Neural Network

Contact Info

Product

Resources

About