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The identification of defect parameters in thermal non-destructive test and evaluation (NDT/E) was considered as a kind of inverse heat transfer problem (IHTP). However, it can be farther considered as a shape optimization problem then a structure design optimization problem, and the design results should meet the surface temperature profile of the apparatus with defects. A bacterial colony chemotaxis...
In this paper, we apply distributed optimization dynamics of the mutually connected neural networks to RAN selection in heterogeneous type cognitive wireless networks. We evaluate the performance of the proposed approach by implementing it on an experimental heterogeneous wireless network system called Cognitive Wireless Cloud, which supports vertical handover between different radio access networks...
A new network for fuzzy-neural system was proposed based on the analysis and comparison of existing methods, which could be easy to distill the fuzzy rules. The network structure was adjusted by FBP(Fuzzy Back Propagation) learning algorithm to acquire network parameters and variable weights. By aiming at disadvantage of IP algorithm on rule-optimization, the Improved Iterative Pruning Neural Network...
The emerging computational grid infrastructure consists of heterogeneous resources in widely distributed autonomous domains, which makes job scheduling very challenging. Although there is much work on static scheduling approaches for workflow applications in parallel environments, little work has been done on a real-world Grid environment for industrial systems. Utility Management Systems (UMS) are...
Artificial neural networks (ANN) and fuzzy systems are the widely preferred artificial intelligence techniques for biological computational applications. While ANN is less accurate than fuzzy logic systems, fuzzy theory needs expertise knowledge to guarantee high accuracy. Since both the methodologies possess certain advantages and disadvantages, it is primarily important to compare and contrast these...
The purpose of this study is to explore how to utilize the artificial neural networks (ANNs) technique to optimize the number, sizes, and locations of reactive power control equipment in order to increase the power system global steady-state stability and security performance. In this paper, two widely used ANNs - multilayer perceptron neural network (MLP) and self-organizing feature map (SOFM) neural...
A new method for the optimal design of the electromagnetic devices is presented. The method utilizes artificial neural networks (ANNs) in a design environment which encompasses numerical computations and expert's input for generating a variety of ANN training data. Results of two implementation examples are provided. The optimal design is obtained quickly (in a matter of milliseconds) once the ANNs...
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