Rule Based Forecasting [RBF] - Improving Efficacy of Judgmental Forecasts Using Simplified Expert Rules

Rule-based Forecasting (RBF) has emerged to be an effective forecasting model compared to well-accepted benchmarks. However, the original RBF model, introduced in1992, incorporates 99 production rules and is, therefore, difficult to apply judgmentally. In this research study, we present a core rule-set from RBF that can be used to inform both judgmental forecasting practice and pedagogy. The simplified rule-set, called coreRBF, is validated by asking forecasters to judgmentally apply the rules to time series forecasting tasks. Results demonstrate that forecasting accuracy from judgmental use of coreRBF is not statistically different from that reported from similar applications of RBF. Further, we benchmarked these coreRBF forecasts against forecasts from (a) untrained forecasters, (b) an expert system based on RBF, and (c) the original 1992 RBF study. Forecast accuracies were in the hypothesized direction, arguing for the generalizability and validity of the coreRBF rules

ARROWSMITH-P: A prototype expert system for software engineering management

Although the field of software engineering is relatively new, it can benefit from the use of expert systems. Two prototype expert systems were developed to aid in software engineering management. Given the values for certain metrics, these systems will provide interpretations which explain any abnormal patterns of these values during the development of a software project. The two systems, which solve the same problem, were built using different methods, rule-based deduction and frame-based abduction. A comparison was done to see which method was better suited to the needs of this field. It was found that both systems performed moderately well, but the rule-based deduction system using simple rules provided more complete solutions than did the frame-based abduction system

Optimization of facility layout

Computer-aided layout technique, which appears to be the best approach to solving complex layout problems, is not commonly used in practice. One of the important reasons may be the generation of unrealistic layouts which results from ignoring the important practical constraints and objectives involved in layout problems. As one possible solution to this problem, a human planner can develop layout using a computer routine with those constraints and objectives in mind. However, the development of a heuristic procedure which incorporates human-like layout processes into a computer program could be a better solution;This dissertation provides the means of a realistic or a close to realistic layout development using important practical objectives and constraints involved in facility layout. Instead of ignoring those factors due to the difficulties of implementing them into mathematical statements, using them in the process of layout development will be helpful to reach an optimum or a near-optimum solution;An experimental system, FLUKES, has been constructed for testing purposes. This system develops layouts which include the practical factors involved in layout problems. These factors include architectural limitations, health/safety, user preferences, utilities, department shapes, future expansion plans, and energy savings as well as material handling costs. FLUKES uses these factors not only for the evaluation of a layout, but also for the search for a solution

The place of expert systems in business now and over the next decade

Information technology has entered a new generation. In recent years, considerable interest has been focussed on the commercialisation of expert systems, which represent an important application of Artificial Intelligence in the field of Information Technology. Expert systems are now in a crucial stage of development because, although in business computerised systems are not new, expert systems still need time for their applicability and usefulness to be proved. The market for expert systems will not develop if such systems are unable to cope with the demanding applications of business; for example with top management problem-solving and decision-making. This thesis is principally concerned with determining the position of expert systems in business by looking at these major business related issues. [Continues.

Modelling of expert nurses' pressure sore risk assessment skills as an expert system for in-service training

In the nursing literature to date there have been no reported applications of `cognitive simulation' nor of intelligent Computer Assisted Learning. In Chapter 1 of this thesis a critical review of existing nurse education by computer is used to establish a framework within which to explore the possibility of simulation of thinking processes of nurses on computer. One conclusion from this review which is offered concerns the importance of firstly undertaking reliable study of nursing cognition. The crucial issue is that an understanding must be gained of how expert nurses mentally represent their patients in order that a valid model might be constructed on computer. The construction of a valid computer based cognitive model proves to be an undertaking which occupies the remainder of this thesis. The approach has been to gradually raise the specificity of analysis of the knowledge base of expert and proficient nurses while seeking concurrently to evaluate validity of the findings. Reported in Chapter 2, therefore, are the several experimental stages of a knowledge acquisition project which begins the process of constructing this knowledge base. Discussed firstly is the choice of the skill domain to be studied - pressure sore risk assessment. Subsequently, the method of eliciting from nurses top-level and micro-level descriptors of patients is set out. This account of knowledge acquisition ends with scrutiny of the performance of nurse subjects who performed a comprehensive simulated patient assessment task in order that two groups might be established - one Expert and one Proficient with respect to the nursing task. In Chapter 3, an extensive analysis of the data provided by the simulated assessment experiment is undertaken. This analysis, as the most central phase of the project, proceeds by degrees. Hence, the aim is to `explain' progressively more of the measured cognitive behaviour of the Expert nurses while incorporating the most powerful explanations into a developing cognitive model. More specifically, explanations are sought of the role of `higher' cognition, of whether attribute importance is a feature of cognition, of the point at which a decision can be made, and of the process of deciding between competing patient judgements. Interesting findings included several reliable differences which were found to exist between the cognition of subjects deemed to be proficient and those taken as expert. In the final part of this thesis, Chapter 4, a more formal evaluation of the computer based cognitive model which was constructed and predictions made by it was undertaken. The first phase involved analysis in terms of process and product of decision making of the cognitive model in comparison to two alternative models; one derived from Discriminant Function Analysis and the other from Automated Rule Induction. The cognitive model was found to most closely approximate to the process of decision making of the human subjects and also to perform most accurately with a test set of unseen patients. The second phase reports some experimental support for the prediction made by the model that nurses represent their patients around action-related `care concepts' rather than in terms of diagnostic categories based on superficial features. The thesis concludes by offering some general conclusions and recommendations for further research

Foundations of Empirical Software Engineering: The Legacy of Victor R. Basili

This book captures the main scientific contributions of Victor R. Basili, who has significantly shaped the field of empirical software engineering from its very start. He was the first to claim that software engineering needed to follow the model of other physical sciences and develop an experimental paradigm. By working on this postulate, he developed concepts that today are well known and widely used, including the Goal-Question-Metric method, the Quality-Improvement paradigm, and the Experience Factory. He is one of the few software pioneers who can aver that their research results are not just scientifically acclaimed but are also used as industry standards. On the occasion of his 65th birthday, celebrated with a symposium in his honor at the International Conference on Software Engineering in St. Louis, MO, USA in May 2005, Barry Boehm, Hans Dieter Rombach, and Marvin V. Zelkowitz, each a long-time collaborator of Victor R. Basili, selected the 20 most important research papers of their friend, and arranged these according to subject field. They then invited renowned researchers to write topical introductions. The result is this commented collection of timeless cornerstones of software engineering, hitherto available only in scattered publications