Search results for: Decision support systems

Authors: Elham Serkani, Hossein Gharaee Garakani, Naser Mohammadzadeh, Elaheh Vaezpour

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Intrusion detection systems (IDS) are the main components of network security. These systems analyze the network events for intrusion detection. The design of an IDS is through the training of normal traffic data or attack. The methods of machine learning are the best ways to design IDSs. In the method presented in this article, the pruning algorithm of C5.0 decision tree is being used to reduce the features of traffic data used and training IDS by the least square vector algorithm (LS-SVM). Then, the remaining features are arranged according to the predictor importance criterion. The least important features are eliminated in the order. The remaining features of this stage, which have created the highest level of accuracy in LS-SVM, are selected as the final features. The features obtained, compared to other similar articles which have examined the selected features in the least squared support vector machine model, are better in the accuracy, true positive rate, and false positive. The results are tested by the UNSW-NB15 dataset.

Keywords: Intrusion detection system, decision tree, support vector machine, feature selection.

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Authors: M. Johnson, R. Faggian, V. Sposito

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A participatory and engaged approach is key in connecting agricultural managers to sustainable agricultural systems to support and optimize production in Victoria’s food bowl. A sustainable intensification (SI) approach is well documented globally, but participation rates amongst Victorian farmers is fragmentary, and key outcomes and implementation strategies are poorly understood. Improvement in decision-support management tools and a greater understanding of the productivity gains available upon implementation of SI is necessary. This paper reviews the current understanding and uptake of SI practices amongst farmers in one of Victoria’s premier food producing regions, the Goulburn Broken; and it spatially analyses the potential for this region to adapt to climate change and optimize food production. A Geographical Information Systems (GIS) approach is taken to develop an interactive decision-support tool that can be accessible to on-ground agricultural managers. The tool encompasses multiple criteria analysis (MCA) that identifies factors during the construction phase of the tool, using expert witnesses and regional knowledge, framed within an Analytical Hierarchy Process. Given the complexities of the interrelations between each of the key outcomes, this participatory approach, in which local realities and factors inform the key outcomes and help to strategies for a particular region, results in a robust strategy for sustainably intensifying production in key food producing regions. The creation of an interactive, locally embedded, decision-support management and education tool can help to close the gap between farmer knowledge and production, increase on-farm adoption of sustainable farming strategies and techniques, and optimize farm productivity.

Keywords: Agriculture, decision-support management tools, GIS, sustainable intensification.

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Authors: Jin-Bao Zhao, Wei Deng

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This paper aims at developing a multilevel fuzzy decision support model for urban rail transit planning schemes in China under the background that China is presently experiencing an unprecedented construction of urban rail transit. In this study, an appropriate model using multilevel fuzzy comprehensive evaluation method is developed. In the decision process, the followings are considered as the influential objectives: traveler attraction, environment protection, project feasibility and operation. In addition, consistent matrix analysis method is used to determine the weights between objectives and the weights between the objectives- sub-indictors, which reduces the work caused by repeated establishment of the decision matrix on the basis of ensuring the consistency of decision matrix. The application results show that multilevel fuzzy decision model can perfectly deal with the multivariable and multilevel decision process, which is particularly useful in the resolution of multilevel decision-making problem of urban rail transit planning schemes.

Keywords: Urban rail transit, planning schemes, multilevel fuzzy decision support model, consistent matrix analysis

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Authors: C. Ardil

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This paper presents preference programming technique based multiple criteria decision making analysis for selecting a facility location for a new organization or expansion of an existing facility which is of vital importance for a decision support system and strategic planning process. The implementation of decision support systems is considered crucial to sustain competitive advantage and profitability persistence in turbulent environment. As an effective strategic management and decision making is necessary, multiple criteria decision making analysis supports the decision makers to formulate and implement the right strategy. The investment cost associated with acquiring the property and facility construction makes the facility location selection problem a long-term strategic investment decision, which rationalize the best location selection which results in higher economic benefits through increased productivity and optimal distribution network. Selecting the proper facility location from a given set of alternatives is a difficult task, as many potential qualitative and quantitative multiple conflicting criteria are to be considered. This paper solves a facility location selection problem using preference programming, which is an effective multiple criteria decision making analysis tool applied to deal with complex decision problems in the operational research environment. The ranking results of preference programming are compared with WSM, TOPSIS and VIKOR methods.

Keywords: Facility Location Selection, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, Preference Programming, Location Selection, WSM, TOPSIS, VIKOR

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Authors: Manpreet Singh, Parvinder Singh, Sumitter Bir Singh

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The emergence of information technology has resulted in an ever-increasing demand to use computers for the efficient management and dissemination of information. Keeping in view the strong need of farmers to collect important and updated information for interactive, flexible and quick decision-making, a model of Decision Support System for Farm Management is developed. The paper discusses the use of Internet technology for the farmers to take decisions. A model is developed for the farmers to access online interactive and flexible information for their farm management. The workflow of the model is presented highlighting the information transfer between different modules.

Keywords: Decision Support System, dissemination.

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Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

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This paper aims to create the model for student in choosing an emphasized track of student majoring in computer science at Suan Sunandha Rajabhat University. The objective of this research is to develop the suggested system using data mining technique to analyze knowledge and conduct decision rules. Such relationships can be used to demonstrate the reasonableness of student choosing a track as well as to support his/her decision and the system is verified by experts in the field. The sampling is from student of computer science based on the system and the questionnaire to see the satisfaction. The system result is found to be satisfactory by both experts and student as well. 

Keywords: Data mining technique, the decision support system, knowledge and decision rules.

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.

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Authors: S. Kamyabi, M. Salari, H. Shahabi

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One of the processes of slope that occurs every year in Iran and some parts of world and cause a lot of criminal and financial harms is called landslide. They are plenty of method to stability landslide in soil and rock slides. The use of the best method with the least cost and in the shortest time is important for researchers. In this research, determining the best method of stability is investigated by using of Decision Support systems. DSS is made for this purpose and was used (for Hasan Salaran area in Kurdistan). Field study data from topography, slope, geology, geometry of landslide and the related features was used. The related data entered decision making managements programs (DSS) (ALES).Analysis of mass stability indicated the instability potential at present. Research results show that surface and sub surface drainage the best method of stabilizing. Analysis of stability shows that acceptable increase in security coefficient is a consequence of drainage.

Keywords: Landslide, Decision Support systems, stability, Hasan Salaran landslide, Kurdistan province, Iran.

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk., L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: Decision making support systems, Emergency risk assessment, Natural and anthropogenic safety, On-line control, Territory.

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Authors: Ferdi Sönmez, Nihal Yorulmaz

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Decision making on the true planning of the public transportation systems to serve potential users is a must for metropolitan areas. To take attraction of travelers to projected modes of transport, adequately fair overall travel times should be provided. In this fashion, other benefits such as lower traffic congestion, road safety and lower noise and atmospheric pollution may be earned. The congestion which comes with increasing demand of public transportation is becoming a part of our lives and making residents’ life difficult. Hence, regulations should be done to reduce this congestion. To provide a constructive and balanced regulation in public transportation systems, right stations should be located in right places. In this study, it is aimed to design and implement a Decision Support System (DSS) Application to determine the optimal bus stop places for public transport in Istanbul which is one of the biggest and oldest cities in the world. Required information is gathered from IETT (Istanbul Electricity, Tram and Tunnel) Enterprises which manages all public transportation services in Istanbul Metropolitan Area. By using the most real-like values, cost assignments are made. The cost is calculated with the help of equations produced by bi-level optimization model. For this study, 300 buses, 300 drivers, 10 lines and 110 stops are used. The user cost of each station and the operator cost taken place in lines are calculated. Some components like cost, security and noise pollution are considered as significant factors affecting the solution of set covering problem which is mentioned for identifying and locating the minimum number of possible bus stops. Preliminary research and model development for this study refers to previously published article of the corresponding author. Model results are represented with the intent of decision support to the specialists on locating stops effectively.

Keywords: User cost, bi-level optimization model, decision support, operator cost, transportation.

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Authors: D. Moser, D. Pinto, A. Cipriano

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A Disaster Management System (DMS) is very important for countries with multiple disasters, such as Chile. In the world (also in Chile)different disasters (earthquakes, tsunamis, volcanic eruption, fire or other natural or man-made disasters) happen and have an effect on the population. It is also possible that two or more disasters occur at the same time. This meansthata multi-risk situation must be mastered. To handle such a situation a Decision Support System (DSS) based on multiagents is a suitable architecture. The most known DMSs are concernedwith only a singledisaster (sometimes thecombination of earthquake and tsunami) and often with a particular disaster. Nevertheless, a DSS helps for a better real-time response. Analyze the existing systems in the literature and expand them for multi-risk disasters to construct a well-organized system is the proposal of our work. The here shown work is an approach of a multi-risk system, which needs an architecture and well defined aims. In this moment our study is a kind of case study to analyze the way we have to follow to create our proposed system in the future.

Keywords: Decision Support System, Disaster Management System, Multi-Risk, Multiagent System.

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Authors: F. Felipe

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Air Defense Systems contain high-value assets that are expected to fulfill their mission for several years - in many cases, even decades - while operating in a fast-changing, technology-driven environment. Thus, it is paramount that decision-makers can assess how effective an Air Defense System is in the face of new developing threats, as well as to identify the bottlenecks that could jeopardize the security of the airspace of a country. Given the broad extent of activities and the great variety of assets necessary to achieve the strategic objectives, a systems approach was taken in order to delineate the core requirements and the physical architecture of an Air Defense System. Then, value-focused thinking helped in the definition of the measures of effectiveness. Furthermore, analytical methods were applied to create a formal structure that preliminarily assesses such measures. To validate the proposed methodology, a powerful simulation was also used to determine the measures of effectiveness, now in more complex environments that incorporate both uncertainty and multiple interactions of the entities. The results regarding the validity of this methodology suggest that the approach can support decisions aimed at enhancing the capabilities of Air Defense Systems. In conclusion, this paper sheds some light on how consolidated approaches of Systems Engineering and Operations Research can be used as valid techniques for solving problems regarding a complex and yet vital matter.

Keywords: Air defense, effectiveness, system, simulation, decision-support.

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Authors: Oscar Fernandez-Flores, Tony Speer, Rodney Day

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This paper identifies five key design characteristics of production scheduling software systems in printed circuit board (PCB) manufacturing. The authors consider that, in addition to an effective scheduling engine, a scheduling system should be able to process a preventative maintenance calendar, to give the user the flexibility to handle data using a variety of electronic sources, to run simulations to support decision-making, and to have simple and customisable graphical user interfaces. These design considerations were the result of a review of academic literature, the evaluation of commercial applications and a compilation of requirements of a PCB manufacturer. It was found that, from those systems that were evaluated, those that effectively addressed all five characteristics outlined in this paper were the most robust of all and could be used in PCB manufacturing.

Keywords: Decision-making, ERP, PCB, scheduling.

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Authors: S.Jerald Jeba Kumar, M.Madheswaran

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The structure of retinal vessels is a prominent feature, that reveals information on the state of disease that are reflected in the form of measurable abnormalities in thickness and colour. Vascular structures of retina, for implementation of clinical diabetic retinopathy decision making system is presented in this paper. Retinal Vascular structure is with thin blood vessel, whose accuracy is highly dependent upon the vessel segmentation. In this paper the blood vessel thickness is automatically detected using preprocessing techniques and vessel segmentation algorithm. First the capture image is binarized to get the blood vessel structure clearly, then it is skeletonised to get the overall structure of all the terminal and branching nodes of the blood vessels. By identifying the terminal node and the branching points automatically, the main and branching blood vessel thickness is estimated. Results are presented and compared with those provided by clinical classification on 50 vessels collected from Bejan Singh Eye hospital..

Keywords: Diabetic retinopathy, Binarization, SegmentationClinical Decision Support Systems.

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Authors: Aseela Alhinaai, Suliman Abdullah, Adil Albusaidi

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Knowledge has been considered an important asset in private and public organizations. It is utilized in the libraries sector to run different operations of technical services and administrative works. This study aims to identify the impact of the knowledge-sharing factors (technology, collaboration, management support) to improve decision-making at Sultan Qaboos University Libraries. This study conducted a quantitative method using a questionnaire instrument to measure the impact of technology, collaboration, and management support on knowledge sharing that lead to improved decision-making. The study population is the Sultan Qaboos University (SQU) libraries (Main Library, Medical Library, College of Economic and Political Science Library, and Art Library). The results showed that management support, collaboration, and technology use have a positive impact on the knowledge-sharing process, and knowledge sharing positively affects decision making process.

Keywords: Knowledge sharing, decision making, information technology, management support, corroboration, Sultan Qaboos University.

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Authors: Chia-Yu Hsu, Julaimin Goh, Pei-Chann Chang

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Home is important for Chinese people. Because the information regarding the house attributes and surrounding environments is incomplete in most real estate agency, most house buyers are difficult to consider the overall factors effectively and only can search candidates by sorting-based approach. This study aims to develop a decision support system for housing purchasing, in which surrounding facilities of each house are quantified. Then, all considered house factors and customer preferences are incorporated into Simple Multi-Attribute Ranking Technique (SMART) to support the housing evaluation. To evaluate the validity of proposed approach, an empirical study was conducted from a real estate agency. Based on the customer requirement and preferences, the proposed approach can identify better candidate house with consider the overall house attributes and surrounding facilities.

Keywords: decision support system, real estate, decision analysis, housing evaluation, SMART

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Authors: Nevena Stolba, A Min Tjoa

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Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Keywords: data mining, data warehousing, decision-support systems, evidence-based medicine.

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Authors: R. Tur, A. Yardımcı

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Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Keywords: Fuzzy logic, decision support systems, construction industry.

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Authors: Rawan A. Abdelrazeq, Ahmed M. Khalafallah, Nabil A. Kartam

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Selection of competent contractors for construction projects is usually accomplished through competitive bidding or negotiated contracting in which the contract bid price is the basic criterion for selection. The evaluation of contractor’s safety performance is still not a typical criterion in the selection process, despite the existence of various safety prequalification procedures. There is a critical need for practical and automated systems that enable owners and decision makers to evaluate contractor safety performance, among other important contractor selection criteria. These systems should ultimately favor safety-conscious contractors to be selected by the virtue of their past good safety records and current safety programs. This paper presents an exploratory sequential mixed-methods approach to develop a framework for an automated decision support system that evaluates contractor safety performance based on a multitude of indicators and metrics that have been identified through a comprehensive review of construction safety research, and a survey distributed to domain experts. The framework is developed in three phases: (1) determining the indicators that depict contractor current and past safety performance; (2) soliciting input from construction safety experts regarding the identified indicators, their metrics, and relative significance; and (3) designing a decision support system using relational database models to integrate the identified indicators and metrics into a system that assesses and rates the safety performance of contractors. The proposed automated system is expected to hold several advantages including: (1) reducing the likelihood of selecting contractors with poor safety records; (2) enhancing the odds of completing the project safely; and (3) encouraging contractors to exert more efforts to improve their safety performance and practices in order to increase their bid winning opportunities which can lead to significant safety improvements in the construction industry. This should prove useful to decision makers and researchers, alike, and should help improve the safety record of the construction industry.

Keywords: Construction safety, contractor selection, decision support system, relational database.

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

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Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Mehmet Altınöz

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This study focuses on bureau management technologies and information systems in developing countries. Developing countries use such systems which facilitate executive and organizational functions through the utilization of bureau management technologies and provide the executive staff with necessary information. The concepts of data and information differ from each other in developing countries, and thus the concepts of data processing and information processing are different. Symbols represent ideas, objects, figures, letters and numbers. Data processing system is an integrated system which deals with the processing of the data related to the internal and external environment of the organization in order to make decisions, create plans and develop strategies; it goes without saying that this system is composed of both human beings and machines. Information is obtained through the acquisition and the processing of data. On the other hand, data are raw communicative messages. Within this framework, data processing equals to producing plausible information out of raw data. Organizations in developing countries need to obtain information relevant to them because rapid changes in the organizational arena require rapid access to accurate information. The most significant role of the directors and managers who work in the organizational arena is to make decisions. Making a correct decision is possible only when the directors and managers are equipped with sound ideas and appropriate information. Therefore, acquisition, organization and distribution of information gain significance. Today-s organizations make use of computer-assisted “Management Information Systems" in order to obtain and distribute information. Decision Support System which is closely related to practice is an information system that facilitates the director-s task of making decisions. Decision Support System integrates human intelligence, information technology and software in order to solve the complex problems. With the support of the computer technology and software systems, Decision Support System produces information relevant to the decision to be made by the director and provides the executive staff with supportive ideas about the decision. Artificial Intelligence programs which transfer the studies and experiences of the people to the computer are called expert systems. An expert system stores expert information in a limited area and can solve problems by deriving rational consequences. Bureau management technologies and information systems in developing countries create a kind of information society and information economy which make those countries have their places in the global socio-economic structure and which enable them to play a reasonable and fruitful role; therefore it is of crucial importance to make use of information and management technologies in order to work together with innovative and enterprising individuals and it is also significant to create “scientific policies" based on information and technology in the fields of economy, politics, law and culture.

Keywords: Bureau Management, Information Systems.

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Authors: Chandrika M.J., Lariyah M.S., Alicia Y.C. Tang

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Ontology is widely being used as a tool for organizing information, creating the relation between the subjects within the defined knowledge domain area. Various fields such as Civil, Biology, and Management have successful integrated ontology in decision support systems for managing domain knowledge and to assist their decision makers. Gross pollutant traps (GPT) are devices used in trapping and preventing large items or hazardous particles in polluting and entering our waterways. However choosing and determining GPT is a challenge in Malaysia as there are inadequate GPT data repositories being captured and shared. Hence ontology is needed to capture, organize and represent this knowledge into meaningful information which can be contributed to the efficiency of GPT selection in Malaysia urbanization. A GPT Ontology framework is therefore built as the first step to capture GPT knowledge which will then be integrated into the decision support system. This paper will provide several examples of the GPT ontology, and explain how it is constructed by using the Protégé tool.

Keywords: Gross pollutant Trap, Ontology, Protégé.

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Authors: Ismail El Gayar, Ossama Ismail, Yousri El Gamal

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This paper presented a technique to solve one of the transportation problems that faces us in real life which is the Bus Scheduling Problem. Most of the countries using buses in schools, companies and traveling offices as an example to transfer multiple passengers from many places to specific place and vice versa. This transferring process can cost time and money, so we build a decision support system that can solve this problem. In this paper, a genetic algorithm with the shortest path technique is used to generate a competitive solution to other well-known techniques. It also presents a comparison between our solution and other solutions for this problem.

Keywords: Bus scheduling problem, decision support system, genetic algorithm, operation planning, shortest path, transportation.

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Authors: Jun-Ho Park, Kwang-Woo Nam, Seung-Mo Hong, Tae-Heon Moon, Sang-Ho Lee, Youn-Taik Leem

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The aim of this study was to build ‘Ubi-Net’, a decision-making support system for systematic establishment in U-City planning. We have experienced various urban problems caused by high-density development and population concentrations in established urban areas. To address these problems, a U-Service contributes to the alleviation of urban problems by providing real-time information to citizens through network connections and related information. However, technology, devices, and information for consumers are required for systematic U-Service planning in towns and cities where there are many difficulties in this regard, and a lack of reference systems. Thus, this study suggests methods to support the establishment of sustainable planning by providing comprehensive information including IT technology, devices, news, and social networking services (SNS) to U-City planners through intelligent searches. In this study, we targeted Smart U-Parking Planning to solve parking problems in an ‘old’ city. Through this study, we sought to contribute to supporting advances in U-Space and the alleviation of urban problems.

Keywords: Design and decision support system, smart U-parking planning, social network analysis.

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Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

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In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

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Authors: Ganesan V.

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Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

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Authors: Mitchell J. McHugh, John J. Case

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Systems engineering is a holistic discipline that seeks to organize and optimize complex, interdisciplinary systems. With the growth of artificial intelligence, systems engineers must face the challenge of leveraging artificial intelligence systems to solve complex problems. This paper analyzes the integration of systems engineering and artificial intelligence and discusses how artificial intelligence systems embody the systems decision process (SDP). The SDP is a four-stage problem-solving framework that outlines how systems engineers can design and implement solutions using value-focused thinking. This paper argues that artificial intelligence models can replicate the SDP, thus validating its flexible, value-focused foundation. The authors demonstrate this by developing a machine vision mobile application that can classify weapons to augment the decision-making role of an Army subject matter expert. This practical application was an end-to-end design challenge that highlights how artificial intelligence systems embody systems engineering principles. The impact of this research demonstrates that the SDP is a dynamic tool that systems engineers should leverage when incorporating artificial intelligence within the systems that they develop.

Keywords: Computer vision, machine learning, mobile application, systems engineering, systems decision process.

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Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

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Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

This paper presents an interval-based multi-attribute decision making (MADM) approach in support of the decision process with imprecise information. The proposed decision methodology is based on the model of linear additive utility function but extends the problem formulation with the measure of composite utility variance. A sample study concerning with the evaluation of electric generation expansion strategies is provided showing how the imprecise data may affect the choice toward the best solution and how a set of alternatives, acceptable to the decision maker (DM), may be identified with certain confidence.

Keywords: Decision Making, Power Generation, ElectricUtilities, Resource Planning.

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