During the development of the intellectual multi-agent investment management information system （designed for the formation of investor＇s investment decisions）, it was established that there is a lack of both neces...During the development of the intellectual multi-agent investment management information system （designed for the formation of investor＇s investment decisions）, it was established that there is a lack of both necessary comprehensive researches and analysis to invoke more than one decision-making aspect （argument） for the making of investment decision, and recommendations to combine these diverse parameters. It is possible to find a lot of articles and researches in which investment decisions or investment tactics are decided on the ground of either technical or fundamental analysis, or modeling and on the ground of intellectual calculating technique （for example, fuzzy logic, neural net, genetic programming）, whereas the issues of the coordination of different techniques are not decided at all. To fill this niche, the article offers the decision applied in multi-agent investment management information system which allows to provide rationale for investment decision taking into account four aspects （arguments）, i.e., to form the recommendation to purchase/hold/sell a security paper having evaluated the following four aspects （arguments）： （a） fundamental analysis, （b） technical analysis, （c） experts and analysts＇ recommendations and （d） risk assessment. These aspects （arguments） are chosen taking into account the real most commonly occurring process of investor＇s investment decision-making. The article gives the implementation of aspects （arguments） assessment by four corresponding software agents whose decisions are implemented with a help of fuzzy logic. Besides, the article offers the technique of the unification of these aspects （arguments）. The offered intellectual multi-agent investment management information system can be tested on the internet： www.sprendimutechnologijos.lt/webapp （MADSYS project）.展开更多
The paper concerns a research into dynamic properties of the steel suspension bridge across Opolska Street in Krakow, Poland. Parameter identification was carried out with the application of the nonlinear system ident...The paper concerns a research into dynamic properties of the steel suspension bridge across Opolska Street in Krakow, Poland. Parameter identification was carried out with the application of the nonlinear system identification method on the basis of system responses to exploitational excitation resulting from pedestrian traffic. In order to verify obtained results, on the basis of the geometrical and material properties of the considered system, the FEM （finite elements model） was created. Created FEM model was updated through the comparison with the model determined by the use of experimental modal analysis method and then applied to analytical evaluation of the considered suspension bridge natural frequencies.展开更多
Despite the fact that progress in face recognition algorithms over the last decades has been made, changing lighting conditions and different face orientation still remain as a challenging problem. A standard face rec...Despite the fact that progress in face recognition algorithms over the last decades has been made, changing lighting conditions and different face orientation still remain as a challenging problem. A standard face recognition system identifies the person by comparing the input picture against pictures of all faces in a database and finding the best match. Usually face matching is carried out in two steps： during the first step detection of a face is done by finding exact position of it in a complex background （various lightning condition）, and in the second step face identification is performed using gathered databases. In reality detected faces can appear in different position and they can be rotated, so these disturbances reduce quality of the recognition algorithms dramatically. In this paper to increase the identification accuracy we propose original geometric normalization of the face, based on extracted facial feature position such as eyes. For the eyes localization lbllowing methods has been used： color based method, mean eye template and SVM （Support Vector Machine） technique. Experimental investigation has shown that the best results for eye center detection can be achieved using SVM technique. The recognition rate increases statistically by 28% using face orientation normalization based on the eyes position.展开更多
The paper present the fuzzy logic expert system called MADSYS for an investor＇s portfolio allocation by financial asset classes. MADSYS system will be used in the interface agent （agents） of multi-agent investment ...The paper present the fuzzy logic expert system called MADSYS for an investor＇s portfolio allocation by financial asset classes. MADSYS system will be used in the interface agent （agents） of multi-agent investment management information system. One of the principal tasks of the multi-agent system is to help an investor to make investment decisions and to provide appropriate investment proposals according to the investor＇s profile. From MADSYS depends a lot of things, namely the multi-agent investment management information system accuracy, proposed investment decisions, the right portfolio allocation of financial assets, reliability and investor satisfaction. The usage of MADSYS system in the multi-agent system makes it more intellectual, i.e. the system will be able to adjust automatically to the changing of investor profile. The MADSYS system may be tried online at the following address：www.sprendimutechnologij os.lt/webapp.展开更多
文摘During the development of the intellectual multi-agent investment management information system （designed for the formation of investor＇s investment decisions）, it was established that there is a lack of both necessary comprehensive researches and analysis to invoke more than one decision-making aspect （argument） for the making of investment decision, and recommendations to combine these diverse parameters. It is possible to find a lot of articles and researches in which investment decisions or investment tactics are decided on the ground of either technical or fundamental analysis, or modeling and on the ground of intellectual calculating technique （for example, fuzzy logic, neural net, genetic programming）, whereas the issues of the coordination of different techniques are not decided at all. To fill this niche, the article offers the decision applied in multi-agent investment management information system which allows to provide rationale for investment decision taking into account four aspects （arguments）, i.e., to form the recommendation to purchase/hold/sell a security paper having evaluated the following four aspects （arguments）： （a） fundamental analysis, （b） technical analysis, （c） experts and analysts＇ recommendations and （d） risk assessment. These aspects （arguments） are chosen taking into account the real most commonly occurring process of investor＇s investment decision-making. The article gives the implementation of aspects （arguments） assessment by four corresponding software agents whose decisions are implemented with a help of fuzzy logic. Besides, the article offers the technique of the unification of these aspects （arguments）. The offered intellectual multi-agent investment management information system can be tested on the internet： www.sprendimutechnologijos.lt/webapp （MADSYS project）.
文摘The paper concerns a research into dynamic properties of the steel suspension bridge across Opolska Street in Krakow, Poland. Parameter identification was carried out with the application of the nonlinear system identification method on the basis of system responses to exploitational excitation resulting from pedestrian traffic. In order to verify obtained results, on the basis of the geometrical and material properties of the considered system, the FEM （finite elements model） was created. Created FEM model was updated through the comparison with the model determined by the use of experimental modal analysis method and then applied to analytical evaluation of the considered suspension bridge natural frequencies.
文摘Despite the fact that progress in face recognition algorithms over the last decades has been made, changing lighting conditions and different face orientation still remain as a challenging problem. A standard face recognition system identifies the person by comparing the input picture against pictures of all faces in a database and finding the best match. Usually face matching is carried out in two steps： during the first step detection of a face is done by finding exact position of it in a complex background （various lightning condition）, and in the second step face identification is performed using gathered databases. In reality detected faces can appear in different position and they can be rotated, so these disturbances reduce quality of the recognition algorithms dramatically. In this paper to increase the identification accuracy we propose original geometric normalization of the face, based on extracted facial feature position such as eyes. For the eyes localization lbllowing methods has been used： color based method, mean eye template and SVM （Support Vector Machine） technique. Experimental investigation has shown that the best results for eye center detection can be achieved using SVM technique. The recognition rate increases statistically by 28% using face orientation normalization based on the eyes position.
文摘The paper present the fuzzy logic expert system called MADSYS for an investor＇s portfolio allocation by financial asset classes. MADSYS system will be used in the interface agent （agents） of multi-agent investment management information system. One of the principal tasks of the multi-agent system is to help an investor to make investment decisions and to provide appropriate investment proposals according to the investor＇s profile. From MADSYS depends a lot of things, namely the multi-agent investment management information system accuracy, proposed investment decisions, the right portfolio allocation of financial assets, reliability and investor satisfaction. The usage of MADSYS system in the multi-agent system makes it more intellectual, i.e. the system will be able to adjust automatically to the changing of investor profile. The MADSYS system may be tried online at the following address：www.sprendimutechnologij os.lt/webapp.
