Application of GA-LM-BP Neural Network in Fault Prediction of Drying Furnace Equipment
نویسندگان
چکیده
منابع مشابه
Fault Diagnosis of Coal Mine Equipment Based on Improved GA Optimized BP Neural Network
In the face of more and more faults in coal mine equipment, this paper presents the method of combining genetic algorithm (GA) and BP neural network to predict the failure. According to genetic algorithm has a very slow convergence speed, easy to fall into local optimum, this paper uses chaos and reverse individual learning initialization, followed by the use of differential algorithm to operat...
متن کاملFault Localization Method Based on Enhanced GA- BP Neural Network
In the process of software development and maintenance, software debugging is the most complicated and expensive part. In recent years, automated software fault localization technology has attracted many scholars’ attention, various approaches have been proposed. In this paper, a technique named EGA-BPN is proposed which can provide suspicious locations for fault localization automatically with...
متن کاملThe Prediction in Computer Color Matching of Dentistry Based on GA+BP Neural Network
Although the use of computer color matching can reduce the influence of subjective factors by technicians, matching the color of a natural tooth with a ceramic restoration is still one of the most challenging topics in esthetic prosthodontics. Back propagation neural network (BPNN) has already been introduced into the computer color matching in dentistry, but it has disadvantages such as unstab...
متن کاملBp Neural Network-Based Effective Fault Localization
In program debugging, fault localization identifies the exact locations of program faults. Finding these faults using an ad-hoc approach or based only on programmers’ intuitive guesswork can be very time consuming. A better way is to use a well-justified method, supported by case studies for its effectiveness, to automatically identify and prioritize suspicious code for an examination of possib...
متن کاملThe Prediction of Food Safety Composite Index based on BP Neural Network and GA Algorithm
The study established a BP neural network prediction model to test the effect of the application to predict the food safety Index. The GA was used to optimize the weights and thresholds of BP neural network. The theoretical analysis and experimental results prove that the BP neural network prediction is feasible for the food safety Index. The index prediction has some value in the field of food...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: MATEC Web of Conferences
سال: 2018
ISSN: 2261-236X
DOI: 10.1051/matecconf/201823201041