• Journal of Information Processing Systems
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• v.6 no.3
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• pp.385-402
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• 2010

Most of the data warehouse (DW) requirements engineering approaches have not distinguished the early requirements engineering phase from the late requirements engineering phase. There are very few approaches seen in the literature that explicitly model the early & late requirements for a DW. In this paper, we propose an AGDI (Agent-Goal-Decision-Information) model to support the early and late requirements for the development of DWs. Here, the notion of agent refers to the stakeholders of the organization and the dependency among agents refers to the dependencies among stakeholders for fulfilling their organizational goals. The proposed AGDI model also supports three interrelated modeling activities namely, organization modeling, decision modeling and information modeling. Here, early requirements are modeled by performing organization modeling and decision modeling activities, whereas late requirements are modeled by performing information modeling activities. The proposed approach has been illustrated to capture the early and late requirements for the development of a university data warehouse exemplifying our model's ability of supporting its decisional goals by providing decisional information.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.549-556
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• 2020

Real estate markets play an essential role in the economic development of both developed and developing countries. Investment decisions in private real estate demand the consideration of several qualitative and quantitative criteria. Especially in Vietnam, demand for housing, apartments are rising which has resulted because of the migration from rural to urban areas. This study aims to determine the influencing factors of the real estate purchasing behavior and then recommend a grey Multi-Criteria Decision Making (MCDM) support model to evaluate real estate alternatives based on a numerical example in Vietnam. A set of essential criteria are identified based on experts' opinion, and the proposed determinants are initial investment, maintenance cost, prestige location, distance to interesting places, parking lot, public transportation, property condition, total area size, number of rooms, and neighbors. The subjective weights were obtained by using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) model, and the Grey Relational Analysis (GRA) technique is employed to prioritize and rank real estate alternatives. The results reveal that this approach can be useful to make purchasing decisions for many kinds of real estate property under uncertain business environments. These findings indicate that the presented hybrid model has advantages in granting flexibility to the preferences of decision makers.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.8-13
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• 2019

Despite technical advances in healthcare, the rates of hospital-acquired pressure injury (HAPI) are still high although many are potentially preventable. The purpose of this study was to determine whether tree-based prediction modeling is suitable for assessing the risk of HAPI in ICU patients. Retrospective cohort study has been carried out. A decision tree model was constructed with Age, Weight, eTube, diabetes, Braden score, Isolation, and Number of comorbid conditions as decision nodes. We used RStudio for model training and testing. Correct prediction rate of the final prediction model was 92.4 and the Area Under the ROC curve (AUC) was 0.699, which means there is about 70% chance that the model is able to distinguish between HAPI and non-HAPI. The results of this study has limited generalizability as the data were from a single academic institution. Our research finding shows that the data-driven tree-based prediction modeling may potentially support ICU sensitive risk assessment for HAPI prevention.

• Journal of Digital Convergence
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• v.11 no.10
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• pp.367-372
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• 2013

In Speech recognition system, there is a problem with phoneme in the model training and it cause a stored mode regeneration process which come into being appear time and more costs. In this paper, we propose the methode of likely phoneme model schema using decision tree clustering. Proposed system has a robust and correct sound model which system apply the decision tree clustering methode form generate model, therefore this system reduce the regeneration process and provide a retrieve the phoneme unit in probability model. Also, this proposed system provide a additional likely phoneme model and configured robust correct sound model. System performance as a result of represent vocabulary dependence recognition rate of 98.3%, vocabulary independence recognition rate of 98.4%.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1257-1270
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• 2016

This study deals with the prediction of the total number of movie audiences as a measure for the box office. Prediction is performed by classification techniques of data mining such as decision tree, multilayer perceptron(MLP) neural network model, multinomial logit model, and support vector machine over time such as before movie release, release day, after release one week, and after release two weeks. Predictors used are: online word-of-mouth(OWOM) variables such as the portal movie rating, the number of the portal movie rater, and blog; in addition, other variables include showing the inherent properties of the film (such as nationality, grade, release month, release season, directors, actors, distributors, the number of audiences, and screens). When using 10-fold cross validation technique, the accuracy of the neural network model showed more than 90 % higher predictability before movie release. In addition, it can be seen that the accuracy of the prediction increases by adding estimates of the final OWOM variables as predictors.

• KDI Journal of Economic Policy
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• v.43 no.4
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• pp.45-67
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• 2021

We analyze the social welfare effect when a policy-based financial system (PFS) enters a decentralized financial market. Particularly, the PFS in this case supports the interest spread for corporate loans held by firms with heterogeneous bankruptcy decisions under an imperfect information structure. Although support for capital costs through the PFS expands the economy consistently, the optimal level of PFS out of the corporate loan market is estimated to be 8.6% by a simulation model considering social welfare adjusted by the disutility of labor. This result is much lower than the recent level of PFS in the Korean financial sector.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.485-496
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• 1997

To develop an Enterprise Data Model in Information Strategy Planning, it is essential that we first decide on the critical entities that need to be consistently managed in the enterprise. Identifying entities is a very crucial decision that has much influence on the subsequent phases in Information Engineering. Nevertheless, it is very subjective and usually depends on a decision makers experience and his/her own knowledge. In this paper, we propose a decision support system called CB*IMSS, which employs Case-Based Reasoning as the problem solution technique. By retrieving, analyzing and adapting some similar previous cases with a decision makers enterprise situations, this system can help them identify and decide the critical entities required for successful performance of the ISP.

• Asia pacific journal of information systems
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• v.5 no.1
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• pp.52-85
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• 1995

This paper develops a new approach to dealing with qualitative reasoning processes involved in managerial decisions, drawing upon choice strategies that have been developed within the general framework of multi-criteria decision making. Issues such as choices under uncertainty and preference formulation are addressed. An MCDM DSS intended to assist in high-level management decisions must focus on helping the decision maker to properly define the problem by providing a structure to it and to dynamically evaluate the alternative courses of action. A conceptual architecture is developed and presented to propose a general model for designing decision support systems specifically designed to assist in MCDM in a managerial context. A commercial loan approval judgment case is described to illustrate the real-world situation where decisions are made under fuzziness and usually require a high degree of intuition and subjective judgment. Development of a prototype system intended to partially represent application of the architecture is described.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.83-88
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• 2024

In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.

• IE interfaces
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• v.13 no.1
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• pp.92-99
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• 2000

Conflicts and interruptions caused by resource failures and rush orders require a nonlinear dynamic production management. Generally the PP&C systems used in industry presently do not meet these requirements because of their rigid concepts. Starting with the grasp of the disadvantages of current approaches, this paper presents a control structure that enables system to react to various malfunctions using a planning tolerance concept. Also, production processes are modeled by using Fuzzy-Petri-Net modeling tool in other to handle the complexity of job allocation and the existence of many disparities. On the basis of this model the developed system support the short-term shop control by rule based decision.