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It is of great significance to carry out cities' air quality forecasting work for the prevention of the air pollution in urban areas and to the improvement of the living environment of urban residents. The air quality index (AQI) is a dimensionless index that quantitatively describes the state of air quality. In this paper, the data of air quality in Lanzhou released by china air quality online monitoring...
Following analyzing existing challenges in addressing the balance between exploration and exploitation encountered by evolutionary algorithms, this paper develops a Genetic Algorithm with speciation (GASP). It first incorporates a novel encoding scheme and recombination method for a balanced genetic divergence when locating global optima in complex applications, such as structural and dynamic design...
Power system stabilizers (PSS) works in conjunction with the excitation system to provide damping of the oscillation of synchronous machine. It has long been recognized as an effective means of curbing low frequency oscillations. Studies reveal that gain setting of the PSS needs to be restricted to a low value in order to ensure that none of the modes are adversely affected with the incorporation...
A new supervised learning algorithm, SNN/LP, is proposed for Spiking Neural Networks. This novel algorithm uses limited precision for both synaptic weights and synaptic delays; 3 bits in each case. Also a genetic algorithm is used for the supervised training. The results are comparable or better than previously published work. The results are applicable to the realization of large-scale hardware neural...
The robustness issue in model-based diagnosis of process faults is addressed by means of artificial neural networks. The symptoms are generated by using observer schemes with dynamic neural nets. Their design is based on a hierarchical genetic algorithm, extended back-propagation method and multiobjective optimisation. The evolutionary search of genetic type is used to find the optimal architecture...
Forecasting is an activity to predict something that has not happened. In the economic sector, banks have the greatest effect on the economy of a country. Sources of bank funds that contribute to the operational activities or lending is third party funding. The third party funding is consist of savings, giro and deposits. The higher the ratio of third party funding, its mean the better public confidence...
Based on the nonlinearity of typhoon intensity, the Locally Linear Embedding (LLE) method is employed to reduce the dimensions of the factors obtained from the climatology and persistence (CLIPER) prediction method for predicting typhoon intensity in the Western Pacific Ocean (WPO). Emulating the theory of the numerical weather prediction in ensemble forecast, a new nonlinear artificial intelligence...
RBF neural network is a single hidden layer of three-front network. Although approximation capacity, classification ability and learning speed of RBF neural network is superior to BP network, it is difficult to find the optimal value of the center point and width as well as the connection threshold, this article uses the immune genetic algorithm to optimize the three parameters of RBF neural network...
The hybridization and application of computational intelligence techniques such as artificial neural networks, fuzzy logic, and genetic algorithms has become hotspot research area in the recent times. This paper presents a work which investigates the benefits of combining genetic algorithms, fuzzy logic and artificial neural networks into a hybrid Neuro Fuzzy Genetic System, especially for the prediction...
According to the special literature, a major research direction to improve the performance level assigned to a pattern recognition system is to use the specific paradigms of artificial intelligence domain. Having as starting point the indubitable advantages given by GANN (Genetic Algorithm Neural Nework) system concept in solving of some concrete pattern recognition tasks, in this paper a comparative...
The problem that how to use hierarchical genetic algorithm to determine the structure and parameters of neural networks was studied. The two grade coding structure of the hierarchical genetic algorithm is utilized to solve the ancient problem that when optimize the neural networks' structure, connection weights, threshold at the same time, the efficiency was low. Furthermore, we compare the networks'...
Sensor Localization is a crucial part of many location??]dependent applications that is utilized in wireless sensor networks (WSNs). Several approaches, including range??]based and range??]free, have been proposed to calculate the position of randomly deployed sensor nodes. With specific hardware, the range??]based schemes typically achieve high accuracy based on either node??]to-node distances or...
Numerous feature selection methods have been developed to identify informative genes from a large pool of genes that are not involved in the array experiments. However, the integrity of the reported genes is still uncertain due to the applications of various pre-processing techniques to the microarray data by these methods and a lack of standard validation procedures to validate the significance of...
Time series forecasting is the main method in network flow prediction. RBF neural network is capable of universal approximation, which not only has fast training velocity, but also can solve the local minima problem. Thus, network flow prediction technology based on genetic algorithm and RBF neural network is presented in the paper. And the training parameters are adjusted by genetic algorithm. Network...
Pressure-Volume-Temperature (PVT) properties are very important in reservoir engineering computations. There are many approaches for predicting various PVT properties based on empirical correlations and statistical regression models. Soft computing techniques and especially artificial neural networks had been utilized in the last decade by researchers to develop more accurate PVT correlations. Unfortunately,...
A new method of neural networks based on genetic algorithm is put forward for factors weight determination of safety assessment in the paper. The procedure on optimizing neural networks by genetic algorithm is expatiated. How to pick up the information of factors weight from the network link weight after training is analyzed in detail. The influence of primary network weight on final determination...
Following the thinking clue of the ensemble prediction in numerical weather prediction (NWP), a novel nonlinear artificial intelligence ensemble prediction (NAIEP) model for calculation wind speed of Mountain Darong in Guangxi has been developed based on the multiple neural networks with identical expected output created by using the genetic algorithm (GA) of evolutionary computation. The results...
A hybrid intelligent fault diagnosis method is presented for the diversity, uncertainty and complexity of device faults. This method integrates respective advantages of fault tree, fuzzy theory, neural networks and genetic algorithms to form a hybrid approach and is applied to fault diagnosis of fan. Experiments show that this method is simple and effective. It can also be applied to other fault diagnosis...
Data mining aims at discovering knowledge out of data and presenting it in a form that is easily compressible to humans. It is a process that is developed to examine large amounts of data routinely collected. Fuzzy systems are been used for solving a wide range of problems in different application domain genetic algorithm for designing. Fuzzy systems allows us to introduce the learning and adaptation...
The use of neural networks (NNs) for financial applications is quite common because of their excellent performances of treating non-linear data with self-learning capability. Often arises the problem of a black-box approach,i.e. after having trained neural networks for a particular problem, it is almost impossible to analyse them for how they work. The Fuzzy Neural Networks(FNN) allow to add rules...
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