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It is very important to forecast the ice thickness of Transmission Line for the safe operation of transmission network. The author had introduced artificial neural network(ANN) to the prediction of the ice thickness of transmission line, and proposed a predictive model based on GA and BP addresses on the defects of BP network includes slow convergence and easiness of running to local minimum, and...
Applications of neural network were widely used in construct project cost estimate. Aim at handling weakness of poor convergence and insufficient forecast, an improved fuzzy neural network method based on SOFM (self-organizing feature map) and GA (genetic algorithm) was proposed to replace the fashionable T-S fuzzy neural network. The method illustrated how to apply SOFM and GA to improve the fault...
Premature convergence is the main obstacle to the application of genetic algorithm. This paper makes improvement on traditional genetic algorithm by linear scale transformation of fitness function, using self-adaptive crossover and mutation probability and adopting close relative breeding avoidance method. Simulation results show that the improved algorithm outperforms traditional genetic algorithm...
In this paper we consider the uplink of a cellular network partitioned into localized jointly decoded cells. These jointly decoded cells are implemented as fixed size clusters. Such networks have a potential for real world deployments with improved spectral efficiency and user experience. Similar to conventional cellular networks, frequency planning can be considered as an efficient method to control...
Evaluation of certain properties of calcined alumina or special grade alumina is necessary and important to its manufactures. Generally it is determined in the laboratories using different instrumental and manual methods, which is cost and time intensive. In the present work, evolving neural network has been used for the estimation of a property given few others. To evolve the neural network model...
Data classification is a prime task in data mining. Accurate and simple data classification task can help the clustering of large dataset appropriately. In this paper we have experimented and suggested a simple ANN based classification models called as minimal ANN (MANN) for different classification problems. The GA is used for optimally finding out the number of neurons in the single hidden layered...
Autofluorescence bronchoscopy (AFB) has been utilized over the past decade, proving to be a powerful tool for the detection and localization of premalignant and malignant lesions of the airways. AFB is, however, characterized by low specificity and a high rate of false positive findings (FPFs). The majority of FPFs are due to inflammations, as they often fluoresce at the same wavelengths with cancer...
This work presents system identification using neural network approaches for modelling a laboratory based twin rotor multi-input multi-output system (TRMS). Here we focus on a memetic algorithm based approach for training the multilayer perceptron neural network (NN) applied to nonlinear system identification. In the proposed system identification scheme, we have exploited three global search methods...
This paper utilizes particle swarm optimization method to train the weights of neural network (NN). Particle swarm optimization (PSO) is a population based stochastic optimization technique. Unlike genetic algorithm (GA), PSO has no evolution operators such as crossover and mutation. Compared to GA, the advantages of PSO are that it is easy to implement and there are few parameters to adjust. In this...
Curved surface renewable solar cell is applied to provide a near space airshippsilas energy system the power to drive the high altitude electromotor and propeller in a long term. The solar flux incident on the solar cell is calculated through integral transform and some revised correlations from tilted surface solar radiation flux calculations. In view of the solar radiation flux and the wind speed...
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