Interpretation Trained Neural Networks Based on Genetic Algorithms
نویسندگان
چکیده
منابع مشابه
Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms
Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...
متن کاملInterpretation of Trained Neural Networks by Rule Extraction
The paper focuses on the problem of rule extraction from neural networks, with the aim of transforming the knowledge captured in a trained neural network into a familiar form for human user. The ultimate purpose for us is to develop human friendly shells for neural network based systems. In the first part of the paper it is presented an approach on extracting traditional crisp rules out of the ...
متن کاملNeural Networks using Genetic Algorithms
Combining neural network with evolutionary algorithms leads to evolutionary artificial neural network. Evolutionary algorithms like GA to train neural nets choose their structure or design related aspects like the functions of their neurons. Along basic concepts of neural networks and genetic algorithm this paper includes a flexible method for solving travelling salesman problem using genetic a...
متن کاملNEURAL NETWORKS AND GENETIC ALGORITHMS NEURAL NETWORKS AND GENETIC ALGORITHMS NEURAL NETWORKS Knowledge Extraction from Local Function Networks
Extracting rules from RBFs is not a trivial task because of nonlinear functions or high input dimensionality. In such cases, some of the hidden units of the RBF network have a tendency to be “shared” across several output classes or even may not contribute to any output class. To address this we have developed an algorithm called LREX (for Local Rule EXtraction) which tackles these issues by ex...
متن کاملA universal VAD based on jointly trained deep neural networks
In this paper, we propose a joint training approach to voice activity detection (VAD) to address the issue of performance degradation due to unseen noise conditions. Two key techniques are integrated into this deep neural network (DNN) based VAD framework. First, a regression DNN is trained to map the noisy to clean speech features similar to DNN-based speech enhancement. Second, the VAD part t...
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: International Journal of Artificial Intelligence & Applications
سال: 2013
ISSN: 0976-2191
DOI: 10.5121/ijaia.2013.4102