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The reasonable evaluation of forestry land is the basis of marketization of the forestry assets. Based on the evaluation data for 325 forestry lands from seven forest farms of Ning'an city, which is intended to transfer in the country, this paper takes Larch, mongolian scots pine and larch-mongolian mixed forests as instances to establish CHAID decision tree model in order to classify and analyze...
Data Mining can find out the hidden important information in mass data, whose main purpose is to help decision-makers to look for the potential relevance between the data, to find out neglected elements, and make decision based on these models automatically. This paper, based on the discussion of data mining, analyzes the framework of enterprise decision support system, designs the enterprise decision...
In order to realize the objective and synthetic evaluation of the feasibility in Low-carbon (LC) project, the paper constructs the knowledge representation system(i.e. attribute value of information system), applies the reduction and the mining rules of the Rough Set Theory, at same the time computing dynamic weight, subjective weight, objective weight are combined with Analytic Hierarchy Process...
Through adopting advanced information techniques, farmers can broaden their information acquisition channels, reduce acquisition cost, and make rational production and operation decisions of production, technology and market information. Based on 117 survey questionnaires from Jiangxi, Fujian and Anhui which have experienced the reform of collective forest right system, this paper specifically takes...
This paper describes the problem of inferring the complex causal relationships among genes from microarray experimental data based on a fuzzy Petri net (FPN). The method derives information on the gene interactions in a highly interpretable form (fuzzy rules) and takes into account dynamical aspects of genes regulation. The approach of the fuzzification of the Petri net is proposed. A token in the...
The paper introduces a formalisation of opportunities, as situations that can be exploited obtaining valuable outcomes, in the context of the social networks, and defines a methodology for discovering opportunities through the analysis of the relation among network actors. The proposed methodology is then applied to the research-oriented networks, whose members share paper coauthorship or potential...
Social networks have generated great expectations connected with their potential business value. The purpose of our research is to present that even a rudimentary application of data mining techniques can bring statistically significant improvement in marketing response accuracy throughout the virtual community. In our test the C&RT (classification and regression tree) approach was used to generate...
Social networks of the Web 2.0 have become global (e.g. FaceBook, MSN). In 1977, L. C. FREEMAN published the first generic metrics for Social Networks Analysis (SNA), mainly based on static graph-mining models. The objective of our work is to introduce new dynamic SNA models dedicated to SNA and to take the conceptual aspects of enterprises and institutions social graph into account. Our work is based...
In this paper, a hybrid network consisting of a trigonometric functional link artificial neural network (FLANN) and fuzzy logic system named as functional link neural fuzzy (FLNF) model is used to predict the stock market indices. The proposed model uses a functional link neural network to the consequent part of the fuzzy rules. The consequent part of FLNF model is a non-linear combination of input...
Modeling of real world financial time series such as stock returns are very difficult, because of their inherent characteristics. ARIMA and GARCH models are frequently used in such cases. It is proven of late that, the traditional models may not produce the best results. Lot of recent literature says the successes of hybrid models. The modeling and forecasting ability of ARFIMA-FIGARCH model is investigated...
Theoretically, e-customers gain more benefit than traditional customers as they can access products and services 24-hours a day from anywhere in the world. However, practically, e-business has not been accepted in spite of its availability and the increased number of internet users in developing countries such as in the Middle East. National cultures combined with other factors affect user acceptance...
A model of the bee hive that clearly separates the self-organizing decision-making behaviour of the bees in the hive and the problem-specific behaviour of the bees outside the hive is presented. This separation allows for the applications of the model for different problem domains. Results of the application to three problem domains are presented - web search, function optimization and hierarchical...
We describe a model-driven translation approach between semantic Web service based business process models in the context of the SUPER project. In SUPER we provide a set of business process ontologies for enabling access to the business process space inside the organisation at the semantic level. One major task in this context is to handle the translations between the provided ontologies in order...
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,...
This paper investigates and analyses the dynamics engendered by the engineering of self-organisation in a global Service Oriented Architecture. The effects are assessed via a resource allocation algorithm for load balancing, based on the observed behaviour of foraging honeybees. It is implemented at the application layer of a simulated server farm type system and its impact is investigated across...
This paper presents some results with application in area of web-based knowledge retrieval. The key issue on the relevant topics retrieving in practice is that the results returned by the actual search engines do not provide fully satisfaction to the user in terms of his or her informational needs. Considering the information utility is correlated to the semantic meaning - that is: if the information...
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 up-to-date segmentation techniques and software programs for microarray image segmentation require human intervention which in turn may detrimentally affect the biological conclusions reached during microarray experiments. In this paper, an automatic approach for segmenting microarray images, based on the morphological modeling of spots, is presented. The conducted experiments have shown that...
Workflow is the most widespread modeling technique application in the field of business and office information systems. In the previous paper introduced P-graph-based workflow modeling extended by the introduction of resource management is a systematic, fast method of optimal workflow model generation based on network synthesis with correct mathematical background. In this paper a further extension,...
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