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There are many factors affect the stability of reservoir slopes, each of them is associated and coupled with others. Generally, the analysis of slopes stability can be achieved by the method of effect-factors analogy and cluster analysis. Traditional cluster analysis is difficult to obtain the stable global optimal solution, since the results are sensitive to the initial cluster center and the order...
Regardless of creation method, Fuzzy rules are of great importance in the implementation and optimization systems. Although using human knowledge in creating Fuzzy rules, has the advantage of readability and is near the experimental expertise, but it cannot be implemented in all systems. Since Output of a system is based on its correct function over the time, output data is reliable with higher percentage...
After studying the disadvantage of BP neural network which has low convergent speed and trap into local minima easily, an idea of designing a new hybrid neural network model. By using Artificial Bee Colony Algorithm (ABC) to expand the updated space of weight and using the fitness functions to decide the better weight. On the basis, make the acquired better value as the weight of BP neural network...
Training of parameters in RBF neural network, this article proposes an optimization of RBF neural network parameters algorithm, which can overcome the disadvantages of select of data center and weights in RBF neural network. The algorithm process input data normalization and compute network output and hidden layer output angle cosine firstly, a set of data being established as the network center when...
An algorithm based on ant colony algorithm for health condition monitoring of aero-engine was put forward. The algorithm conversed the health status classification of aero-engine into solving the clustering-based optimization problem with constrain. Ant colony algorithm based on colony collaboration and learning could solve this clustering problem. The proposed algorithm was applied to monitor health...
The Alcoholism is an addictive disorder, which causes social, physical, psychiatric and neurological damages on individuals. In this paper, Global Field Synchronization (GFS) measurements of multi channel ERP (Event Related Potential) signals in Delta, Theta, Alpha, Beta and Gamma frequency bands are used as discriminating feature vectors in the classification of alcoholic and non-alcoholic control...
Ant Colony Optimization (ACO) metaheuristic is a recent population-based approach inspired by the observation of real ants colony and based upon their collective foraging behavior. In This paper, the proposed technique ACO hybrid with Fuzzy segmentation. In the first step, the MRI brain image is Segmented Aco Hybrid with Fuzzy method to extract the suspicious region. In the second step deals with...
This paper identifies the key aspects of perishable food distribution problem in metropolis. A multi-objective model of vehicle routing problem with time window is constructed including fixed vehicle cost, operation cost, shelf life loss and default cost. In order to reduce the increase distribution cost via meeting the time window, two-generation Ant Colony Optimization with ABC customer classification...
Each HIV-1 patient has a diverse population of virus strains in his/her body as the virus quickly replicates and mutates, requiring a combination drug therapy optimized to the patient's unique viral population. Towards this goal, prediction systems have been developed to deduce the susceptibility of a given HIV genotype to a single drug. Many are rule-based systems or rely on hand-crafted features...
Spatial clustering is very relevant to its sample distribution, clustering geometry configuration and spatial structure. Hierarchy dividing of spatial clustering and its optimization has been studied based on K-means algorithm in this paper. It recommends a classical method of hierarchy dividing of spatial clustering and a new rule to optimize the k value of spatial clustering. The rule and its expansibility...
The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users...
Network intrusion detection system needs to handle huge data selected from network environments which usually contain lots of irrelevant or redundant features. It makes intrusion detection with high resource consumption, as well as results in poor performance of real-time processing and intrusion detection rate. Without loss of generality, feature selection can effectively improve the classification...
The existence of fake tea from non-origin impacts on the credibility and sales of the origin Longjing tea seriously. In order to weaken this impact, we proposed a technology using ant colony clustering algorithm in discrimination the origin of Longjing tea. Then acquired and analyzed the characteristics of the origin tea comprehensively, the 16 parameters of the images and spectra from each sample...
Classification of items taken from data streams requires algorithms that operate in time sensitive and computationally constrained environments. Often, the available time for classification is not known a priori and may change as a consequence of external circumstances. Many traditional algorithms are unable to provide satisfactory performance while supporting the highly variable response times that...
Rare categories abound and their characterization has heretofore received little attention. Fraudulent banking transactions, network intrusions, and rare diseases are examples of rare classes whose detection and characterization are of high value. However, accurate characterization is challenging due to high-skewness and non-separability from majority classes, e.g., fraudulent transactions masquerade...
Many applications such as pattern recognition require selecting a subset of the input features in order to represent the whole set of features. The aim of feature selection is to remove irrelevant or redundant features while keeping the most informative ones. In this paper, an ant colony system approach for solving feature selection for classification is presented. The proposed algorithm was tested...
Rule-based classifiers have been successfully applied in data mining applications. In this Paper, we have proposed a novel rule generator classifier called CORER (Colonial competitive Rule-based classifier) to improve the accuracy of data classification. The proposed classifier works based on CCA (Colonial Competitive Algorithm), a recently-developed evolutionary optimization algorithm. In order to...
The selection of a classifier is only one aspect of the problem of data classification. Equally important (if not, more so) is the pre-processing strategy to be employed. In this paper, a pre-processing step is proposed in order to increase accuracy of classification. The objective of this pre-processing step is to achieve a high degree of separation among classes before the classifier is trained...
In this paper we propose a rough classification modeling algorithm based on Ant Colony Optimization (ACO) reduction. We used ACO to compute the rough set reduct and later a modified rules generation method is employed to generate the classification rules. The rules generation algorithm used is the simplification of the Default Rules Generation Framework (DRGF) in order to fit with the ACO reduct....
This paper proposes a new feature-selection strategy by integrating the Rough Set Theory (RST) and Particle Swarm Optimisation (PSO) algorithms to generate a set of discriminatory features for the classification problem. The proposed method is seen as a marriage between filter and wrapper approaches in which the RST is used to pre-reduce the feature set before optimisation by PSO, a meta-heuristic...
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