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Artificial neural network is an important research direction in data mining. It is used to solve classification and regression problems, and can find out the nonlinear relation between the input attribute and the output attribute, especially the smooth and continuous nonlinear relations. Use the Microsoft neural network to find out how the meteorological factors influence the precipitation, and to...
Data mining technique is an effective tool used to obtain desired knowledge from massive data. Neural network is a new method in the application of data mining. Although it may have shortcomings of complex structure, long training time and uneasily understandable representation of results, neural network has high accuracy which is superior to other methods and this makes it more available in data...
Aiming at the shortages of the existing data-mining model for forecasting the industry security, a classification model based on rough sets and BP neural network (BPNN) is put forward in this paper. First, the theory of rough set is applied to pick up and reduce the index attributes. Then, the training samples are sent to the BPNN to train and learn. After that, the sorts of the coal industry security...
Telecom broadband is a main channel supporting internet surfing in China. With the market competition development, customer churn management has become a kernel task of marketing for telecommunication operators. The traditional market research methods are difficult to support the challenge of churn. Data mining techniques are applied to the customer churn management, to establish an early-warning...
The following topics are dealt with: data hiding techniques; wavelet transform; management information system; image sequence compressing algorithm; trusted software; case-based reasoning system; education information platform; UML; multiobjective optimization; information retrieval; web mining; CUDA architecture; fuzzy association rules; BP neural network; network security detection method; adaptive...
This paper presents a comparison of data mining techniques for wind power forecasting in a time frame out to 15 minutes ahead. The forecasting is focused on the power generated by the wind farms and the power changes are predicted by using multivariate time series models ARMA, focus time-delay neural network (FTDNN) and a phenomenological model of the turbines. All these models are tested with real...
In the last years, artificial intelligence has been an important field as the environments in which human-made devices have to operate become more and more complex, and designing a new algorithm for each environment can be very time and resources consuming. Neural networks have been successful in a lot of applications, since the same basic implementation can be used in a virtually unlimited number...
Insolvency of insurance companies has been a concern to the community due to the need to protect the general public from the aftermath of insurer insolvency and to try to minimize the costs associated to this difficulty such as the insurance guaranty funds. The artificial neural network is utilized in this study to create an insolvency predictive model that could predict any future failure of general...
Jet Grouting (JG) is a Geotechnical Engineering technique that is characterized by a great versatility, being the best solution for several soil treatment improvement problems. However, JG lacks design rules and quality control. As the result, the main JG works are planned from empirical rules that are often too conservative. The development of rational models to simulate the effect of the different...
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...
This paper discusses neural network technique for fault diagnosis of a cracked cantilever beam. In the neural network system there are six input parameters and two output parameters. The input parameters to the neural network are relative deviation of first three natural frequencies and first three mode shapes. The output parameters of the neural network system are relative crack depth and relative...
Due to the advent of computer technology image-processing techniques have become increasingly important in a wide variety of applications. This is particularly true for medical imaging such as Computer Tomography (CT), magnetic resonance image (MRI), and nuclear medicine, which can be used to assist doctors in diagnosis, treatment, and research This paper presents a novel method to extract salient...
A central problem in marketing is the clear understanding of consumer's choice or preferences. This is achieved by designing questionnaires and then analyzing the answers of would be customers. The traditional approach in the conjoint analysis has been the designing of non-adaptive questionnaires. The questionnaire is predetermined and not at all influenced by respondent's answers. This paper aims...
Pattern theorem in financial time-series is one of the most important technical analysis methods in financial prediction. Recent researches have achieved big progresses in identifying and recognizing time-series patterns. And most of the recent works on time-series deal with this task by using static approaches and mainly focus on the recognition accuracy, but considering that recognition of patterns...
Predicting university admission is a complex decision making process that is more than merely relying on test scores. It is known by researchers that students' backgrounds and other factors correlate to the performance of their tertiary education. This paper proposes a hybrid model of neural network and decision tree classifier that predicts the likelihood of which university a student may enter,...
The following topics are dealt with: knowledge expertise system; e-learning; Web-based group decision support system; adaptive neuro fuzzy inference system; e-government; wireless sensor networks; geographical information system; knowledge discovery; and recommender systems.
The aim of this paper is to describe an alternative analytical method in order to evaluate customer outage cost (COC) in Thailand. The information of electrical expense, outage frequency, outage duration, and process recovery time from industrial customers is gathered. They are used to be inputs of the proposed adaptive neuro fuzzy inference system (ANFIS). In the data training by neural network,...
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...
The following topics are dealt with: neural networks; equalisation; mobile and cellular communications; optical communications; data security; human factors in communications; coding and modulation; optical networks; database and optimisation; time-frequency analysis; computer vision and recognition; audio and speech processing; wireless networks; watermarking; digital filters; network coding and...
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