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Register a new userThe Role of Knowledge in Decision Support Systems
دور المعرفة في أنظمة اتخاذ القرار
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نقترح في هذه المقالة طريقة مبنية بشكل أساسي على نظرية البينات لمعالجة المعلومات الهجينة بأنواعها المختلفة الكمية و النوعية و الترتيبية و الثنائية .. إلخ، مع تنوع عيوبها مثل عدم الدقة و الغموض و الاحتمالية و الضياع، .. الخ، مع عد التعارض الناتج عن مصادرها المختلفة في الأنظمة الأمنية بهدف استنباط المعارف و اتخاذ القرارات ابتداء من عناصر المعطيات الناتجة عن المصادر (الحساسات)، و ذلك بالاعتماد على قواعد الحالات Case bases التي تحتوي على حالات أمنية مسبقة اتخذت قرارات مناسبة لكل منها، و من ثم يمكن لهذه القواعد أن تشكل مصدراً إضافياً للمعلومات مع الحساسات و مصادر المعلومات الأخرى بهدف تحسين فهم النظام و أدائه. ستُشرح الطريقة المقترحة بمثال رقمي توضيحي بالتفصيل لفهم الأساس الرياضي للموديل الرياضي المقترح.
In this article, we propose a mathematical model, fundamentally based on evidence theory in order to process and to combine the information elements coming from different sources of information in a security system. These elements could be heterogeneous (qualitative, quantitative, ordinal, binary … etc.) and imperfect (imprecise, ambiguous, probable, missing values … etc.). Along with the heterogeneity and the imperfection, we must consider the case bases that contain security cases with solutions to help us to make decisions as supplementary sources of information (this is called in machine learning field ''case-based reasoning''). Furthermore, the proposed method must consider the conflict and the contradictory resulting from the different sources of evidence. The afore-mentioned issues will be explained through an illustrative numeric example to clarify the proposed model.
References used
Fayyad, U., Piatetsky-Shapiro, G., Smyth, P., From data mining to knowledge discovery in databases, AI magazine, 17(3), (1996), 37–54
Solaiman, B., Information Fusion Concepts: From Information Elements Definition to the Application of Fusion Approaches, SPIE proceedings series, 4385, (2001), 205-212
Smarandache F., Dezert J., Advances and Applications of DSmT for Information Fusion, part I, American Research Press Rehoboth, 1, (2004), Chapters 1-6
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Educational data mining aims to study the available data in the educational field and extract the hidden knowledge from it in order to benefit from this knowledge in enhancing the education process and making successful decisions that will improve th
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The study aimed to identify the relationship between the technical, human, and
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The researcher used the comprehensive inventory of all the banks in the Syri
an Coast style,
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regulatory abilities, have a role on the adoption of decision support system in the Syrian
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adopt a decision support systems. Then some of the recommendations show up for
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systems directly linked to the senior management at the banks in the Syrian Coast, and let
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greater attention to human abilities available to use the decision support systems like:
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The use of traditional methods to analyze massive amounts of
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patterns supports the decision-making process So the purpose
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analysis of data sets through the use of automated analysis,
which includes many of the techniques such as assembly
process (clustering) and Altnsnev (classification) and the
correlation base (association Rule) And the process of visual
data exploration techniques Manifesting, and then the
comparison with other data sets manifestation techniques and
evaluation of the proposed Manifesting system.
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Through this research, we aim at showing the notions related to the knowledge economy and at the diagnosis of its practical fact in Algeria by presenting the principal challenges that faced this new type of economy and by looking for the mechanisms which must be adopted by the state in order to overcome these obstacles.
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