The research project, currently in progress, aims at developing a decision support system for assisting the decision maker to rank reconditioning projects in hydropower plants. The paper focuses on the conceptual fram...
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The research project, currently in progress, aims at developing a decision support system for assisting the decision maker to rank reconditioning projects in hydropower plants. The paper focuses on the conceptual framework of such a decision support system. Theories and methods from decision analysis are considered. The structure of the concept is based on a model of the decision process.
managing software development and maintenance projects requires early knowledge about quality and effort needed for achieving this quality level. Quality-based productivity management is introduced as one approach for...
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managing software development and maintenance projects requires early knowledge about quality and effort needed for achieving this quality level. Quality-based productivity management is introduced as one approach for achieving and using such process knowledge. Fuzzy rules are used as a basis for constructing quality models that can identify outlying software components that might cause potential quality problems. A special fuzzy neural network is introduced to obtain the fuzzy rules combining the metrics as premises and quality factors as conclusions. Using the law of DeMorgan, this net structure is able to learn premises just by changing the weights. Note that the authors change neither the number of neurons nor the number of connections. This new type of net allows for the extraction of knowledge acquired by training on the past process data directly in the form of fuzzy rules. Beyond that, it is possible to transfer all the known rules to the neural fuzzy system in advance. The suggested approach and its advantages towards common simulation and decision techniques is illustrated with experimental results. Its application area is in maintenance productivity. A module quality model-with respect to changes-provides both quality of fit (according to past data) and predictive accuracy (according to ongoing projects).
The present work deals with R&D engineering project management. Classical mechanisms and tools for project management are presented and a systemic model is proposed emphasizing the study of qualitative multidimens...
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The present work deals with R&D engineering project management. Classical mechanisms and tools for project management are presented and a systemic model is proposed emphasizing the study of qualitative multidimensional relationships between systems and subsystems. The proposed model defines five main systems (or "environments"): the organization, the project, the customer, the "project management tools and techniques", and "other associated projects". Such a model provides a qualitative framework for analysis and observations of complex situations usually found in R&D projects. The relationships are not restricted to the mechanisms and techniques generally applied, but a holistic and systemic approach is considered regarding other factors like inter-personnel conflicts and exchanges. In order to optimize and to establish better definitions for the system's and relationships of the proposed model, a qualitative and exploratory field-research was carried out among some Brazilian organizations developing R&D projects.
Often a user that solves a problem with the support of a system (knowledge-based system, software, etc.), must intervene to overcome the limited capabilities of the system. We aim to introduce a type of intelligent As...
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ISBN:
(纸本)0818657804
Often a user that solves a problem with the support of a system (knowledge-based system, software, etc.), must intervene to overcome the limited capabilities of the system. We aim to introduce a type of intelligent Assistant systems (IASs) between the user and the system. The IAS will acquire the knowledge that permits the user to solve problems and will after use it for solving similar problems to relieve the user's interventions. Thus, the IAS builds in an incremental manner a `personal' knowledge base that is a kind of `user-in-action' model. IASs must accomplish a number of tasks, in one hand for managing knowledge (e.g., acquisition, assimilation, validation), and, in the other hand, for managing interaction with the user (e.g., dialogue management, explanation, cooperation). It is not realistic to tackle the design of IASs in one shot. The keystone of our approach lies on the observation that tasks have not the same importance in each application and on the fact that tasks are used incrementally. We present an approach to design IASs from several applications. This permit to: (1) Generalize the results obtained in each application;(2) Share results among applications. We follow since two years such an approach on the basis of four applications in different domains (power systems, banking, genetics, alarm control monitoring). We contrast our approach with large projects that are developed in the same spirit.
We describe MESA, a domain-independent interactive tool for the development of reusable causal models and model-based-reasoning applications. Our current efforts are focused on developing automated sensor monitoring a...
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ISBN:
(纸本)0818650702
We describe MESA, a domain-independent interactive tool for the development of reusable causal models and model-based-reasoning applications. Our current efforts are focused on developing automated sensor monitoring applications for NASA flight projects. MESA supports model development from a component-centered approach and provides a graphical editor for rapidly prototyping components and connections from a small set of modeling primitives that describe structure and behavior (e.g., quantity, mechanism). Causal models, as used in Artificial Intelligence, contain interdependent structural and behavioral descriptions of the system being modeled. MESA also provides a model-based discrete-event simulator that can predict future behavior of the system from knowledge of the current behavior of the model. MESA thereby allows models to be tested, debugged and deployed within one generic environment.
Although several methods for economic justification of general information system and office automation system are well documented, research on the feasibility of using these methods in justifying intelligentsystems ...
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Reported by the author is an expert system which enhances the capability of a nonlinear optimization program. Included are discussions on the knowledge acquisition aspect and the advantageous use of neural networks to...
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The integration of neural networks and expert systems creates the potential for systems that are more powerful than ones using either of the techniques alone. The project presented uses hybrid systems for analyzing co...
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Educational Research in Data Abstractions (ERDA) is an intelligent tutorial system. The system's focus is to present animated and graphical representations of data abstractions and algorithms to supplement CS2 lec...
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