• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.109-116
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• 2005

Proposed in this paper is an intelligent management system for evaluating science research projects based on fuzzy neural networks with genetic algorithms. This system was planned, designed and tested employing theories and approaches of software engineering. This system was then applied to evaluate science research projects of the Natural Science Foundation of Guangdong Province, People’s Republic of China. The outcome / results shows the feasibility and validity of the system and its possible application to other intelligent management systems.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.257-261
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• 2003

In this study, we investigated the modeling and design of an Intelligent Agent System (IAS). To achieve this goal, we introduced several kinds of agents that exhibit intelligent features. These are the main agent, management agent, watcher agent, report agent and application agent. We applied the intelligent agent concept to two different application fields, i.e. the intelligent agent system for pattern classification and the intelligent agent system for bank asset management modeling.

• The Journal of Information Systems
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• v.2
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• pp.194-206
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• 1993

Intelligent remote learning system is a system that incorporate communication technology and others : a database engine, an intelligent tutorial system. Learners can study by themselves through the intelligent tutorial system. The existence of a communication, database and artificial intelligence enhance the capability of IRLS. According to Parsaye, an intelligent databases should have the following features : 1) Knowledge discovery. 2) Data integrity and quality control. 3) Hypermedia management. 4) Data presentation and display. 5) Decision support and scenario analysis. 6) Data format management. 7) Intelligent system design tools. I hope that this research of framework for IRLS paves for the future research. As mentioned in the above, the future work will include an intelligent database, self-learning mechanism using neural network.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.81-86
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• 2001

In this paper, we investigated the modeling of Bank Asset Management System(BAME) based on intelligent agent. To achieve this goal, we introduced several kinds of agents that show intelligent features. BAMS is a user friendly system and adopts fuzzy converting system and fuzzy matching system that returns reasonable similarity matching results. Generation function of the proximity degree is suggested. Fuzzification of investment type categories and feature values are defined, and generation of proximity degree is also derived. An example of bank asset management system is introduced and simulated. Investment type matching utilizing fuzzy measure is tested and it showed quite reasonable similarity matching results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.3
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• pp.322-331
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• 2013

This paper describes the development of the pilot plant of distributed intelligent management system for a microgrid. For optimal control and management of microgrids, intelligent agents area applied to the microgrid management system. Each agent includes intelligent algorithms to make decisions on behalf of the corresponding microgrid entity such as distributed generators, local loads, and so on. To this end, each agent has its own resources to evaluate the system conditions by collecting local information and also communicating with other agents. This paper presents key features of the data communication and management of the developed pilot plant such as the construction of mesh network using local wireless communication techniques, the autonomous agent coordination schemes using plug-and-play functions of agents and contract net protocol (CNP) for decision-making. The performance of the pilot plant and developed algorithms are verified via real-time microgrid test bench based on hardware-in-the-loop simulation systems.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.225-230
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• 2022

The intelligent home network system integrates various devices in the home into one communication network to provide information sharing, control, and operation environment between devices. This intelligent home network system operates around a home server. Home appliances in the era of the 4th industrial revolution will have numerous home servers in logical areas as the intelligent home network in the home accelerates. Therefore, the need for systematic management of home servers is emerging. We propose an agent system for efficient intelligent smart home server management. The agent system monitors the home server and operating environment for home server management of the intelligent smart home network. By referring to this monitored information, the service module of the home server is managed, and the home server is dealt with whether it is normal or not. In addition, by referring to the information collected by the service agent created in the group management server while migrating the home server, it is possible to deal with integrated meter reading, crime prevention, and topics. And when a new service is applied to the home server, it is registered in the management server and distributed to the home server through the agent, so that the intelligent smart home network can be efficiently managed.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.77-104
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• 1995

Intelligent Decision System support the decision analysis process in the managerial problems with decision analytic knowledge as well as domain specific knowledge. Influence Diagram has been one of the major knowledge representation in the intelligent decision system. In the development of intelligent decision system, knowledge acquisition is also known to be difficult. This paper suggests a developing tool using an influence diagram and Verbal Protocol Analysis which facilitates knowledge acquision for intelligent decision system. An ennvironmental decision making problem is used as an illustrative example and validation of the suggested developing tool is discussed. The suggested tool is very flexible to be expanded or applied to similar problems.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.763-769
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• 2022

Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.162-169
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• 2009

The real-time traffic data is generated continuous and unbounded stream data type while intelligent transport system (ITS) needs to provide various and high quality services by combining with spatial information. Traditional database techniques in ITS has shortage for processing dynamic real-time stream data and static spatial data simultaneously. In this paper, we design and implement an advanced traffic monitoring system (ATMS) with the integration of existed data stream management system (DSMS) and spatial DBMS using IntraMap. Besides, the developed ATMS can deal with the stream data of DSMS, the trajectory data of relational DBMS, and the spatial data of SDBMS concurrently. The implemented ATMS supports historical and one time query, continuous query and combined query. Application programmer can develop various intelligent services such as moving trajectory tracking, k-nearest neighbor (KNN) query and dynamic intelligent navigation by using components of the ATMS.