Converter end-point prediction model using spectrum image analysis and improved neural network algorithm
نویسندگان
چکیده
Aiming at the present situation of the steelmaking end-point control at home and abroad, a neural network model was established to judge the end-point. Based on the colour space conversion and the fiber spectrum division multiplexing technology, a converter radiation multi-frequency information acquisition system was designed to analyze the spectrum light and image characteristic information, and the results indicate that they are similar at early-middle stage but dissimilar when approach the steelmaking blowing end. The model was trained and forecasted by using an improved neural network correction coefficient algorithm and some appropriate variables as the model parameters. The experimental results show the proposed algorithm improves the prediction accuracy by 15.4% over the conventional algorithm in 5 s errors and the respond time is about 1.688 s, which meets the requirements of end-point judgment online.
منابع مشابه
Natural Gas Price Forecasting using Kriging Interpolation Technique and Neldar-Mead Optimization Algorithm
The prediction of economic series with high volatility and high uncertainty - such as natural gas prices - is always a challenge in econometric models, because the use of traditional linear modeling models does not allow us to predict complex and nonlinear time series. Regarding the prediction of natural gas prices, findings point to superiority of the neural network compared to regression mod...
متن کاملPrediction of Surface Roughness by Hybrid Artificial Neural Network and Evolutionary Algorithms in End Milling
Machining processes such as end milling are the main steps of production which have major effect on the quality and cost of products. Surface roughness is one of the considerable factors that production managers tend to implement in their decisions. In this study, an artificial neural network is proposed to minimize the surface roughness by tuning the conditions of machining process such as cut...
متن کاملAn Artificial Neural Network Model for Prediction of the Operational Parameters of Centrifugal Compressors: An Alternative Comparison Method for Regression
Nowadays, centrifugal compressors are commonly used in the oil and gas industry, particularly in the energy transmission facilities just like a gas pipeline stations. Therefore, these machines with different operational circumstances and thermodynamic characteristics are to be exploited according to the operational necessities. Generally, the most important operational parameters of a gas pipel...
متن کاملPrediction of Driver’s Accelerating Behavior in the Stop and Go Maneuvers Using Genetic Algorithm-Artificial Neural Network Hybrid Intelligence
Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption....
متن کاملImproving biological activity prediction of protein kinase inhibitors using artificial neural network and partial least square methods
Introduction: Protein kinase causes many diseases, including cancer; therefore, inhibiting them plays an important role in the treatment of many diseases. Traditional discovery inhibitors of this enzyme is a time-consuming and costly process. Finding a reliable computer-aided drug discovery tools which can detect the inhibitors will reduce the cost. In this study, it is attempted to separate ki...
متن کامل