The Experts below are selected from a list of 4233 Experts worldwide ranked by ideXlab platform
Jun Oga - One of the best experts on this subject based on the ideXlab platform.
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Business Fluctuation and the sport industry in japan an analysis of the sport industry from 1986 to 1993
1998Co-Authors: Jun OgaAbstract:The purpose of this study was to assess the extent to which the Japanese sport industry was affected by Business Fluctuations in the domestic economy during the 1986-1993 Business cycle. In addition, the relations between changes in the general economy (gross domestic product, combined sector in the economic activities, family income, living expenditures, and working hours) and the value of the sport industry were investigated. The annual figures for these variables were derived from several government and nongovernment publications, and the percentage changes in these variables were used in multiple regression analysis. Analysis indicated that the trend in value of the sport industry was affected by the Fluctuations and demonstrated positive correlation with the changes in the combined sector in the general economy. However, the trend in value of the sport industry was not correlated with trends in family income or living expenditures during the period under observation. Subsequent analysis of the sports...
H C Chen - One of the best experts on this subject based on the ideXlab platform.
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an application of intelligent neural network to time series Business Fluctuation prediction
1994Co-Authors: A Satyadas, H C ChenAbstract:Economy is a dynamic system that inherits nonlinearity through long term trends, seasonal patterns, cyclical movements, and irregular factors. Time series prediction of Business cycle indicators plays a critical role in managing an economy. Artificial neural network models have been successfully applied with univariate time series, multivariate datasets, classification techniques, and integrated techniques that incorporate various methods for economy prediction. Flexible intelligent systems for soft computing (FISSC) allow dynamic multi-level reasoning and inference using a fuzzy neural multicriteria group decision making framework. This paper focus on the application of the FISSC intelligent neural module to time series economy prediction. The neural module performance is evaluated in terms of convergence, generalization, scalability, sensitivity, and structural stability using the USA Business cyclical indicator data set. This data set includes the lead, lag, and coincidental indicators that span over 420 months. The results are presented and the authors conclude with a discussion on their ongoing research direction. >
L I Chaoxian - One of the best experts on this subject based on the ideXlab platform.
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research on the relation between retail Business Fluctuation and economic reform
2004Co-Authors: L I ChaoxianAbstract:This paper reviews the track of retail Business Fluctuation, probes into the relation between retail Business Fluctuation and economic reform and discusses restrain of economic reform implement and influence of its time choice.
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the characteristic and classification of the retail Business Fluctuation in china
2004Co-Authors: L I ChaoxianAbstract:This article systematically analyzes the characteristics of retail Business Fluctuation according to the present condition in China. On the basis of the analysis it also makes sone classification in the hope to provide some valuable reperences to the governments in their decision-making process.
A Satyadas - One of the best experts on this subject based on the ideXlab platform.
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an application of intelligent neural network to time series Business Fluctuation prediction
1994Co-Authors: A Satyadas, H C ChenAbstract:Economy is a dynamic system that inherits nonlinearity through long term trends, seasonal patterns, cyclical movements, and irregular factors. Time series prediction of Business cycle indicators plays a critical role in managing an economy. Artificial neural network models have been successfully applied with univariate time series, multivariate datasets, classification techniques, and integrated techniques that incorporate various methods for economy prediction. Flexible intelligent systems for soft computing (FISSC) allow dynamic multi-level reasoning and inference using a fuzzy neural multicriteria group decision making framework. This paper focus on the application of the FISSC intelligent neural module to time series economy prediction. The neural module performance is evaluated in terms of convergence, generalization, scalability, sensitivity, and structural stability using the USA Business cyclical indicator data set. This data set includes the lead, lag, and coincidental indicators that span over 420 months. The results are presented and the authors conclude with a discussion on their ongoing research direction. >
L I Yongyou - One of the best experts on this subject based on the ideXlab platform.
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analysis on the relations between Business Fluctuation and fiscal policy Fluctuation in china fiscal policy discretion vs automatic stabilizers
2006Co-Authors: L I YongyouAbstract:Based on efficient measurement of Business Fluctuation and fiscal policy Fluctuation, this paper utilizes impulse response and linear regression to analyze the relations between them quantitatively. It is found that, since 1978, their Fluctuations have been quite similar interfering with each other, but fiscal revenue and expenditure Fluctuation elicited by Business Fluctuation is asymmetric, which can be explained as a major cause of fiscal deficit since 1994. Two-way Granger causality doesn't exist between them completely, elicited fiscal revenue and expenditure have smaller influences on Business Fluctuation, and there exists an evident time-lag. Although discretionary fiscal policy has shorter time-lag, coordination failure exists evidently between revenue and expenditure policy; their effects on Business are asymmetric. As long as efficacy is concerned, expansionary policy is better than contractive policy, discretion better than stabilizers
