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In order to increase the accuracy of abnormal event detection in crowd video surveillance, this paper proposes a novel hybrid optimization of feature selection and support vector machine (SVM) training model based on genetic algorithm. For reducing dimensions of multi-feature, we propose an adaptive genetic simulated annealing algorithm (ASAGA) feature selection method. The ASAGA takes advantage of...
In this paper we train an Artificial Neural Network (ANN) using Memetic Algorithm (MA) and evaluate its performance on the UCI spambase dataset. The Memetic algorithm incorporates the local search capacity of Simulated Annealing (SA) and the global search capability of Genetic Algorithm (GA) to optimize the parameters of the ANN. The performance of the MA is compared with traditional GA in training...
A meme in the context of optimization represents a unit of algorithmic abstraction that dictates how solution search is carried out. At a higher level, a meta-meme serves as an encapsulation of the scheme of interplay between memes involved in the search process. This paper puts forth the notion of neural meta-memes to extend the collective capacity of memes in problem-solving. We term this as Neural...
Price index forecasting is one of the most important problems in financial markets. In the past decades the prediction of stock index has played a vital role in the financial situation of several companies which have stocks in the market. In this paper we use Multi Layer Perceptron (MLP) neural network in stock index prediction. Three searching algorithms were used to get the best network architecture...
In pursuit of better CRTh2 receptor antagonist agents, 2D-QSAR, 3D- QSAR studies were performed on a series of 2,4-disubstituted-phenoxy acetic acid derivatives. The best QSAR model was selected, having correlation coefficient R = 0.904, standard error of estimation SEE = 0.456 and cross validated squared correlation coefficient Q2 = 0.739. The predictive ability of the selected model was also confirmed...
In this paper, a novel classification approach is presented. This approach uses fuzzy if-then rules for classification task and employs a hybrid optimization method to improve the accuracy and comprehensibility of obtained outcome. The mentioned optimization method has been formulated by simulated annealing and genetic algorithm. In fact, the genetic operators have been used as perturb functions at...
Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local minimum, the genetic algorithm and simulated annealing algorithm with the overall search capability have been put forward to optimize authority value and threshold value of BP nerve network. In this paper, a new neural network model which is optimized by genetic algorithm...
Since the BP neural network algorithm has some unavoidable disadvantages, such as slowly converging speed and easily running into local infinitesimal, the genetic algorithm and simulated annealing algorithm with the overall search capability has been put forward to optimize authority value and threshold value of BP nerve network. In this paper, GA-SA neural network algorithm model has been established...
A support vector machines method (SVM) is presented for the hourly load forecasting of the coming days. In this approach, improved SVM based on simulated annealing algorithm and genetic algorithm. The new approach is used for the next day load forecast. These two methods are combined to find the improved parameters for Support Vector Machine. It proves that the combined method is useful in improve...
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