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The aim of the work is verifying the possibility of extrapolating information on demand trends, for a company specialized in the production of aluminium tins, using the data collected in previous periods. This study is mainly divided into three stages: (1) data pre-processing (data collection) stage, (2) adaptive network evaluating stage and (3) forecast and recall stage. At the stage of data collection,...
Energy plays a fundamental role in an economy. Turkey has the world's 15th largest GDP-Purchasing power parity and 17th largest Nominal GDP. Economists and political scientists classify Turkey as a newly industrialized country. In this study, an alternative model for Turkey's energy consumption is proposed for the time between 1980 and 2004. Artificial neural network based model (ANN) is preferred...
The crude oil demand is growing rapidly in China, driven by its rapid industrialization and motorization. China has already become the second-largest oil importer nation in the world, after the United States. The dynamic GM(1,1) model of grey theory is used to develop the dynamic GM(M,N) model to forecast the crude oil consumption and production in China. In order to improve the forecasting accuracy,...
To meet the challenge of knowledge-based economy in the 21st century, scientifically evaluating the innovation capability is important to strengthening the international competence and acquiring long-term competitive advantage for Chinese enterprises. In the article, based on the description of concept and structure of enterprise's innovation capability, the evaluation index system of innovation capability...
In this paper we want to provide a decision-making model for cluster enterprises to select partners. Previous studies are more based on enterprises' capabilities, we studies from a new perspective of credit assessment. First, we established a credit assessment index system of cluster enterprises' partners, it analyzed a candidate enterprise from three parts as strength credibility, honesty credibility...
With the rapid development of economy part of which is devoted by coal mines, safety evaluation can not be the perfect method to promote the safety level of coal industry especially when factors holding back safe production come up. Thus the early-warning system must be established so as to send out signals before disaster happens. Artificial neural network is the basis in this article to set up early-warning...
The bio-hydrogen producing process has complex interactions; thus, constructing a detailed mechanistic model and proper control architecture is difficult. Artificial neural networks (ANNs) are capable of inferring the complex relationships between input and output process variables without a detailed characterization of the mechanisms governing the process. This work presented a novel ANN that accurately...
In view of the existing problems of investment risks evaluation on high-tech industry projects such as a lack of systematic, with too much subjectivity and from the point to improve evaluation efficiency and effectiveness, the paper combined analytic hierarchy process (AHP) with BP neural network to establish a new and suitable risk evaluation model of high-tech projects. Firstly, we applied AHP to...
Based on the theory of system engineering, coal mine production safety has been analyzed. From workers, production process, coal production and economy, coal mine production safety evaluation indexes have been confirmed, and then the BP neural network model of coal mine production safety evaluation has been built. After training and testing the model, the model can accurately evaluate the coal mine...
Measures programming is an important way for improving the effect of measures of oil fields, which can extend the stable production age limit of oil fields, reduce the mining difficulty and improve oil-producing speed and final recovery ratio. Based on the theory of stochastic chance-constrained goal programming, a stochastic chance-constrained goal programming model is put forward for measures programming...
Proposed cement clinker strength forecasting model based on rough set & neural network by analyzing the dangers of clinker strength detecting lag and the current forecasting means & methods with many shortcomings and limitations. The model makes good use of the advantage of rough set identifiable matrix attribute reduction and neural network good at dealing with non-linear problem. After training...
Grey relational analysis (GRA) has been widely applied in analysing multivariate time series data (MTS). It is an alternate solution to the traditional statistical limitations. GRA is employed to search for grey relational grade (GRG) which can be used to describe the relationships between the data attributes and to determine the important factors that significantly influence some defined objectives...
Coal is a key of basic energy in China, and it supports the rapid development of the national economy. In the coming period, coal will also play the very important role in base energy. Therefore, the prediction of coal demand is particularly important in future. In this paper, the double hidden layers BP neural network is established and simulated based on Matlab technology. After testing actual data,...
Construction of container terminal is complex for natural circumstances, regional economic conditions and other related regional transport system and economy. In order to comprehensively appraising investment feasibility of container terminal, an approach adaptable to evaluate construction of container terminal is presented after analysis of container terminal transportation system. Meanwhile a corresponding...
The stope structure parameters and grade indices of underground metal mine are concerned to the safety, economy and sociality of the whole mine. The conventional methods to ascertain above parameters are generally according to experience and analogy, which has artificial blindness. Metal mine exploitation is a complex system engineering, the whole mine system includes many subsystems, and some of...
With the growing international food crisis, grain production and supply have become an important task. Information technology (IT) can help developing countries forecast their grain production. The Generalized Regression Neural Network (GRNN) model is a good technique for predicting grain production in rural areas. Using real agricultural data from Tianjin Binhai area, the agricultural production...
The quantitative relation between output in gross national production (GNP) contributed by science & technology and its input can be constituted. The key methods are to get production distributed by contribution rate of science & technology, to separate input of science & technology from all the inputs for producing GNP respectively using Douglas and Cobb growth model, and then to set...
In this paper, we consider a multiperiod fuzzy production and sourcing problem that a manufacturer has a number of plants and subcontractors. The manufacturer has to meet the products demand according to the service level requirements set by its customers. The demand for each product in each period is assumed to be a fuzzy variable. Since the proposed model is too complex that the conventional optimization...
The output distance function is a key concept in economics. However, its empirical estimation is less than satisfactory because it often violates properties dictated by economic theory. In this paper we introduce the neural distance function (NDF) which constitutes a global approximation to any arbitrary production technology with multiple outputs given by a neural network (NN) specification and imposes...
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