As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To ove...As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To overcome this challenge, technology forecasting isconsidered as a powerful tool in today's business environment, while there are as many successstories as there are failures, a good application of this method will give a good result. Amethodology of integration of patterns or lines of technology evolution in TRIZ parlance ispresented, which is also known as TRIZ technology forecasting, as input to the QFD process to designa new product. For this purpose, TRIZ technology forecasting, one of the TRIZ major tools, isdiscussed and some benefits compared to the traditional forecasting techniques are highlighted. Thena methodology to integrate TRIZ technology forecasting and QFD process is highlighted.展开更多
Since Manufacturing Execution System (MES) is a bridge which links the upper planning system of the enterprise and the control system of the shop floor, various kinds of the information with different characteristics ...Since Manufacturing Execution System (MES) is a bridge which links the upper planning system of the enterprise and the control system of the shop floor, various kinds of the information with different characteristics flow through the system. The information environment of MES and its effect on MES scheduling are analyzed. A methodological proposal is given to address the problem of agile scheduling in a complex information environment, based on which a microeconomic market and game theoretic model-based scheduling approach is presented. The future development of this method is also discussed.展开更多
The difficulty in crude oil price forecasting, due to inherent complexity, has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forec...The difficulty in crude oil price forecasting, due to inherent complexity, has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting crude oil prices. However, all of the existing models of prediction can not meet practical needs. Very recently, Wang and Yu proposed a new methodology for handling complex systems-TEI@I methodology by means of a systematic integration of text mining, econometrics and intelligent techniques.Within the framework of TEI@I methodology, econometrical models are used to model the linear components of crude oil price time series (i.e., main trends) while nonlinear components of crude oil price time series (i.e., error terms) are modelled by using artificial neural network (ANN) models. In addition, the impact of irregular and infrequent future events on crude oil price is explored using web-based text mining (WTM) and rule-based expert systems (RES) techniques. Thus, a fully novel nonlinear integrated forecasting approach with error correction and judgmental adjustment is formulated to improve prediction performance within the framework of the TEI@I methodology. The proposed methodology and the novel forecasting approach are illustrated via an example.展开更多
Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whe...Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study.The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.展开更多
Artificial neural networks (ANNs) have been widely used as a promising alternative approach for forecast task because of their several distinguishing features. In this paper, we investigate the effect of different sam...Artificial neural networks (ANNs) have been widely used as a promising alternative approach for forecast task because of their several distinguishing features. In this paper, we investigate the effect of different sampling intervals on predictive performance of ANNs in forecasting exchange rate time series. It is shown that selection of an appropriate sampling interval would permit the neural network to model adequately the financial time series. Too short or too long a sampling interval does not provide good forecasting accuracy. In addition, we discuss the effect of forecasting horizons and input nodes on the prediction performance of neural networks.展开更多
The focus of research on Agricultural Economics and Management (AEM) has been switching from de-veloped countries to developing countries. In important international journals on AEM such as ""American Jour-n...The focus of research on Agricultural Economics and Management (AEM) has been switching from de-veloped countries to developing countries. In important international journals on AEM such as ""American Jour-nal of Agricultural Economics"" and ""Agricultural Eco-nomics"", the research objectives mainly focus on AEM problems in developing countries, e.g. the effects ofglobalization and liberalization on agricultural produc-tion in developing countries, and problems in agricul-tural resources and environmental protections in devel-oping countries.展开更多
In this paper, we convert the linear complementarity problem to a system of semismooth nonlinear equations by using smoothing technique. Then we use Levenberg-Marquardt type method to solve this system. Taking advanta...In this paper, we convert the linear complementarity problem to a system of semismooth nonlinear equations by using smoothing technique. Then we use Levenberg-Marquardt type method to solve this system. Taking advantage of the new results obtained by Dan, Yamashita and Fukushima [11, 33], the global and local superlinear convergence properties of the method are obtained under very mild conditions. Especially, the algorithm is locally superlinearly convergent under the assumption of either strict complementarity or certain nonsingularity. Preliminary numerical experiments are reported to show the efficiency of the algorithm.展开更多
基金This project is supported by National Natural Science Foundation of China(No.20172041) and Provincial Science Foundation of Anhui, China (No.03042308).
文摘As a result of the fierceness of business competition, companies, to remaincompetitive, have to charm their customers by anticipating their needs and being able to rapidlydevelop exciting new products for them. To overcome this challenge, technology forecasting isconsidered as a powerful tool in today's business environment, while there are as many successstories as there are failures, a good application of this method will give a good result. Amethodology of integration of patterns or lines of technology evolution in TRIZ parlance ispresented, which is also known as TRIZ technology forecasting, as input to the QFD process to designa new product. For this purpose, TRIZ technology forecasting, one of the TRIZ major tools, isdiscussed and some benefits compared to the traditional forecasting techniques are highlighted. Thena methodology to integrate TRIZ technology forecasting and QFD process is highlighted.
基金Supported by the National Natural Science Foundation of China(50105006 )National Hi-tech R&D Program of China (2001AA412140 and 2003AA411120)
文摘Since Manufacturing Execution System (MES) is a bridge which links the upper planning system of the enterprise and the control system of the shop floor, various kinds of the information with different characteristics flow through the system. The information environment of MES and its effect on MES scheduling are analyzed. A methodological proposal is given to address the problem of agile scheduling in a complex information environment, based on which a microeconomic market and game theoretic model-based scheduling approach is presented. The future development of this method is also discussed.
基金This research is partially supported by NSFC, CAS, RGC of Hong Kong and Ministry of Education and Technology of Japan
文摘The difficulty in crude oil price forecasting, due to inherent complexity, has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting crude oil prices. However, all of the existing models of prediction can not meet practical needs. Very recently, Wang and Yu proposed a new methodology for handling complex systems-TEI@I methodology by means of a systematic integration of text mining, econometrics and intelligent techniques.Within the framework of TEI@I methodology, econometrical models are used to model the linear components of crude oil price time series (i.e., main trends) while nonlinear components of crude oil price time series (i.e., error terms) are modelled by using artificial neural network (ANN) models. In addition, the impact of irregular and infrequent future events on crude oil price is explored using web-based text mining (WTM) and rule-based expert systems (RES) techniques. Thus, a fully novel nonlinear integrated forecasting approach with error correction and judgmental adjustment is formulated to improve prediction performance within the framework of the TEI@I methodology. The proposed methodology and the novel forecasting approach are illustrated via an example.
基金This paper was partially supported by NSFC,CAS,RGC of Hong Kong and Ministry of Education and Technology of Japan.
文摘Various mathematical models have been commonly used in time series analysis and forecasting. In these processes, academic researchers and business practitioners often come up against two important problems. One is whether to select an appropriate modeling approach for prediction purposes or to combine these different individual approaches into a single forecast for the different/dissimilar modeling approaches. Another is whether to select the best candidate model for forecasting or to mix the various candidate models with different parameters into a new forecast for the same/similar modeling approaches. In this study, we propose a set of computational procedures to solve the above two issues via two judgmental criteria. Meanwhile, in view of the problems presented in the literature, a novel modeling technique is also proposed to overcome the drawbacks of existing combined forecasting methods. To verify the efficiency and reliability of the proposed procedure and modeling technique, the simulations and real data examples are conducted in this study.The results obtained reveal that the proposed procedure and modeling technique can be used as a feasible solution for time series forecasting with multiple candidate models.
基金This research is Partially supported by NSFC, CAS. MADIS and RGC of Hong Kong.
文摘Artificial neural networks (ANNs) have been widely used as a promising alternative approach for forecast task because of their several distinguishing features. In this paper, we investigate the effect of different sampling intervals on predictive performance of ANNs in forecasting exchange rate time series. It is shown that selection of an appropriate sampling interval would permit the neural network to model adequately the financial time series. Too short or too long a sampling interval does not provide good forecasting accuracy. In addition, we discuss the effect of forecasting horizons and input nodes on the prediction performance of neural networks.
文摘The focus of research on Agricultural Economics and Management (AEM) has been switching from de-veloped countries to developing countries. In important international journals on AEM such as ""American Jour-nal of Agricultural Economics"" and ""Agricultural Eco-nomics"", the research objectives mainly focus on AEM problems in developing countries, e.g. the effects ofglobalization and liberalization on agricultural produc-tion in developing countries, and problems in agricul-tural resources and environmental protections in devel-oping countries.
文摘In this paper, we convert the linear complementarity problem to a system of semismooth nonlinear equations by using smoothing technique. Then we use Levenberg-Marquardt type method to solve this system. Taking advantage of the new results obtained by Dan, Yamashita and Fukushima [11, 33], the global and local superlinear convergence properties of the method are obtained under very mild conditions. Especially, the algorithm is locally superlinearly convergent under the assumption of either strict complementarity or certain nonsingularity. Preliminary numerical experiments are reported to show the efficiency of the algorithm.
