摘要:

AbstractAutomatic order matching systems have emerged as an electronic alternative to traditional markets. In current automatic order matching systems, price and quantity are the only product dimensions used for the order matching. However, a single‐commodity market is made up of many heterogeneous goods which are close to each other but different in qualities and delivery conditions. Price and quantity are important but represent only parts of product attributes that commodity traders want to take into account. This study aims to extend current automatic order matching systems by diversifying product dimensions. Anintelligent order matching systemnot only maximizes the total transaction volume based on the price and quantity but also satisfies traders' qualitative preferences over attributes other than price and quantity. The intelligent order matching mechanism combines an economic model with a preference model to incorporate both quantitative and qualitative utility of market participants.Constraint logic programmingis investigated as a new information technology to structure and implement the intelligent order matching system.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00076.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractFinancial options and futures give investors the opportunity to form complex strategies that meet their investment objectives for risk management. However, this opportunity gives rise to a difficult task: finding a desired strategy from among a large number of possible strategies. This paper describes an intelligent decision‐support system for generating option‐based investment strategies by using constraint programming, which is an integrated framework of Artificial Intelligence and Logic Programming. In this system, constraint programming acts as a bridge between qualitative and quantitative analyses in decision processes. In qualitative analysis, logical reasoning with hypotheses is used to automatically create complex strategies through abstract matching with investors' profiles. Here, abstract matching can be regarded as symbolic computation for producing qualitatively reasonable strategies. In quantitative analysis, a set of complete solutions that satisfy user‐supplied constraints are obtained by constraint satisfaction and optimization. A constraint language based on the framework of Constraint Logic Programming has been developed in order to integrate these symbolic and numerical computations in a uniform way. The resulting system written in this language has the following features. (1) Unlike rule‐based expert systems, the constraint‐based system can create novel investment strategies. (2) A smooth transition from qualitative to quantitative analyses can be naturally achieved due to the constraint language. (3) Qualitative analysis can reduce search complexity, because the analysis focuses on a small set of qualitative distinctions in solution space. These features indicate the usefulness of constraint programming for designing intelligent decision‐support systems.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00077.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractWe present a new approach to evaluation of bankruptcy risk of firms based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of information systems representing knowledge gained by experience. The financial information system describes a set of objects (firms) by a set of multi‐valued attributes (financial ratios and qualitative variables), called condition attributes. The firms are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of firms by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the firms analysed and to derive decision rules from the financial information system which can be used to support decisions about financing new firms. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of bankruptcy risk by a Greek industrial development bank is studied using the rough set approach.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00078.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractThe Information Technology (IT) for realizing Organizational Decision Support Systems (ODSS) is in a nascent stage of development. This is particularly true in the area of coordination, which is a critical element of ODSS, and which distinguishes ODSS research from earlier research in Group DSS and individually oriented DSS. As a first step in ODSS coordination research, alternative representation schemes need to be examined in terms of both their match with the prevailing needs of organizations and of existing IT approaches that can be brought to bear. Matching ODSS needs with coordination representation requirements is examined by using several supporting reference disciplines including foundational DSS and recent ODSS research frameworks/architectures. Existing IT approaches are adapted from the reference disciplines of Active DSS, Distributed Artificial Intelligence (DAI), and Mathematical/Computational Organization Theory (MCOT) to operationalize a computational model of coordination that: (1) embodies the philosophies of Active DSS—including the idea that automated intelligent agents can play a significant role in supporting decision makers by independently carrying out rudimentary tasks to support the various phases of a decision making process; (2) adapts DAI and IT approaches to reflect practical human organizational realities including what we refer to as the ‘Open‐Ended Knowledge World‘, and the evolutionary nature of organizations—whereby ODSS coordination representations will be subjected to almost constant revision due to both external environment disruptions and internal events that require adjustments to a preliminary plan; and (3) reflects the fact that organizational goals are often vague, which implies that a coordination representation should be sufficiently robust to reflectad hocanalysis accommodating of strategy changes.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00079.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractWhile advanced computing technology, and particularly the use of artificial intelligence in the form of expert systems, could not necessarily be said to be common in the US financial planning domain, it is certainly not unheard of. This situation is significantly different from that found in the comparable UK domain. This paper is based on a project to look at the use of computing technology to support the role of the personal financial adviser in the UK—a domain in which little published research work has been undertaken. It briefly describes the current UK marketplace and details the construction of a small hybrid‐based expert system, built to support the selection of personal pension plans, to illustrate the inherent value in developing such technology in this domain. The paper discusses the benefits of using hybrid representational techniques as opposed to single representations in creating an expert system in a financial planning domain.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00080.x

出版商:Wiley    

年代:2014

数据来源: WILEY

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00081.x

出版商:Wiley    

年代:2014

数据来源: WILEY

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1995.tb00082.x

出版商:Wiley    

年代:2014

数据来源: WILEY