Benny Raphael

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This paper presents a new algorithm called PGSL Probabilistic Global Search Lausanne. PGSL is founded on the assumption that optimal solutions can be identified through focusing search around sets of good solutions. Tests on benchmark problems having multi-parameter non-linear objective functions revealed that PGSL performs better than genetic algorithms(More)
A system identification methodology that makes use of data mining techniques to improve the reliability of identification is presented in this paper. An important aspect of the methodology is the generation of a population of candidate models. Indications of the reliability of system identification are obtained through an examination of the characteristics(More)
Good prediction of the behavior of wind around buildings improves designs for natural ventilation in warm climates. However wind modeling is complex, predictions are often inaccurate due to the large uncertainties in parameter values. The goal of this work is to enhance wind prediction around buildings using measurements through implementing a(More)
System identification involves identification of a behavioral model that best explains the measured behavior of a structure. This research uses a strategy of generation and iterative filtering of multiple candidate models for system identification. The task of model filtering is supported by measurement cycles. During each measurement cycle, the location(More)
System identification using multiple-model strategies may involve thousands of models with several parameters. However, only a few models are close to the correct model. A key task involves finding which parameters are important for explaining candidate models. The application of feature selection to system identification is studied in this paper. A new(More)
Many engineering tasks involve the search for good solutions among many possibilities. In most cases, tasks are too complex to be modeled completely and their solution spaces often contain local minima. Therefore, classical optimization techniques cannot, in general, be applied effectively. This paper studies two stochastic search methods, one(More)
This paper presents three CBR systems that have been developed over seven years in collaboration with two industrial partners. In this research, case based reasoning (CBR) is used to compute costs of construction projects. In contrast with previous work in the field of CBR, the focus is on choosing strategies that are compatible with user needs and(More)
Cluster validity indices are used for both estimating the quality of a clustering algorithm and for determining the correct number of clusters in data. Even though several indices exist in the literature, most of them are only relevant for data sets that contain at least two clusters. This paper introduces a new bounded index for cluster validity called the(More)