Pub Date : 2001-06-25DOI: 10.1109/SMCIA.2001.936739
F. Sahin, J. Bay
This paper proposes a decision-theoretic intelligent agent model to solve a herding problem and studies the learning from experience capabilities of the agent model. The proposed intelligent agent model is designed by combining Bayesian networks (BN) and influence diagrams (ID). The online Bayesian network learning method is proposed to accomplish the learning from experience. Intelligent agent software, IntelliAgent, is written to realize the proposed intelligent agent model and to simulate the agents in a problem domain. The same software is then used to simulate the herding problem with one sheep and one dog. Simulation results show that the proposed intelligent agent is successful in establishing a goal (herding) and learning other agents' behaviors.
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Pub Date : 2001-06-25DOI: 10.1109/SMCIA.2001.936719
S. Kercel, M. Klein, B. Pouet
A persistent problem in the analysis of Lamb wave signatures in experimental data is the fact that several different modes appear simultaneously in the signal. The modes overlap in both frequency and time domains. Attempts to separate the overlapping Lamb wave signatures by conventional signal processing methods have been unsatisfactory, As might be expected, the transient nature of Lamb waves makes them readily tractable to wavelet analysis. The authors have used the discrete wavelet transform and the wavelet packet transform to untangle the Lamb wave signature. Furthermore, both techniques are realizable in the highly parallel cascaded-lattice architecture, and are well suited for on-line real-time instrumentation. For signatures of Lamb waves captured in laser ultrasonic data in tailor-welded blanks, this has led to straightforward detection of weld defects and demonstration of principle that weld defects can be classified according to the type of defect as revealed by features in wavelet space. This technique has considerable commercial value for online monitoring of manufacturing processes. For example, laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties butt-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels.
{"title":"Wavelet and wavelet-packet analysis of Lamb wave signatures in real-time instrumentation","authors":"S. Kercel, M. Klein, B. Pouet","doi":"10.1109/SMCIA.2001.936719","DOIUrl":"https://doi.org/10.1109/SMCIA.2001.936719","url":null,"abstract":"A persistent problem in the analysis of Lamb wave signatures in experimental data is the fact that several different modes appear simultaneously in the signal. The modes overlap in both frequency and time domains. Attempts to separate the overlapping Lamb wave signatures by conventional signal processing methods have been unsatisfactory, As might be expected, the transient nature of Lamb waves makes them readily tractable to wavelet analysis. The authors have used the discrete wavelet transform and the wavelet packet transform to untangle the Lamb wave signature. Furthermore, both techniques are realizable in the highly parallel cascaded-lattice architecture, and are well suited for on-line real-time instrumentation. For signatures of Lamb waves captured in laser ultrasonic data in tailor-welded blanks, this has led to straightforward detection of weld defects and demonstration of principle that weld defects can be classified according to the type of defect as revealed by features in wavelet space. This technique has considerable commercial value for online monitoring of manufacturing processes. For example, laser-based ultrasonic (LBU) measurement shows great promise for on-line monitoring of weld quality in tailor-welded blanks. Tailor-welded blanks are steel blanks made from plates of differing thickness and/or properties butt-welded together; they are used in automobile manufacturing to produce body, frame, and closure panels.","PeriodicalId":104202,"journal":{"name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128266715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-06-25DOI: 10.1109/SMCIA.2001.936726
L. Frosini, G. Petrecca
A system identification method based on black-box techniques for the prediction of the electric energy consumption in a dairy firm is presented. This prediction is required by the Italian free energy market where the energy sellers aim at selling energy according to a load flow scheduled some days in advance. The black-box identification is employed as an alternative to an energy investigation of the firm. The inputs of the system are the work shifts of each process unit and the output is the electric energy consumption. Two black-box parametric models have been evaluated-linear and neural-and the principal component analysis method has been employed to preprocess the data.
{"title":"System identification for the prediction of the electric energy consumption of a dairy firm","authors":"L. Frosini, G. Petrecca","doi":"10.1109/SMCIA.2001.936726","DOIUrl":"https://doi.org/10.1109/SMCIA.2001.936726","url":null,"abstract":"A system identification method based on black-box techniques for the prediction of the electric energy consumption in a dairy firm is presented. This prediction is required by the Italian free energy market where the energy sellers aim at selling energy according to a load flow scheduled some days in advance. The black-box identification is employed as an alternative to an energy investigation of the firm. The inputs of the system are the work shifts of each process unit and the output is the electric energy consumption. Two black-box parametric models have been evaluated-linear and neural-and the principal component analysis method has been employed to preprocess the data.","PeriodicalId":104202,"journal":{"name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131601398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2001-06-25DOI: 10.1109/SMCIA.2001.936745
N.H. Eklund, M. Embrechts
This paper presents an improved method for determining the optimal filter (with respect to efficiency) to move a lamp from its "natural" position in color space to an arbitrary position in color space. Compared to a fixed parameter GA application employing the "chromosome smoothing operator" the use of fuzzy control of some GA parameters and application specific mutation methods leads to a substantial reduction in the number of function evaluations required, while maintaining the same overall level of solution quality.
{"title":"Employing fuzzy logic and problem specific mutation methods to boost the performance of spectrum optimization via genetic algorithms","authors":"N.H. Eklund, M. Embrechts","doi":"10.1109/SMCIA.2001.936745","DOIUrl":"https://doi.org/10.1109/SMCIA.2001.936745","url":null,"abstract":"This paper presents an improved method for determining the optimal filter (with respect to efficiency) to move a lamp from its \"natural\" position in color space to an arbitrary position in color space. Compared to a fixed parameter GA application employing the \"chromosome smoothing operator\" the use of fuzzy control of some GA parameters and application specific mutation methods leads to a substantial reduction in the number of function evaluations required, while maintaining the same overall level of solution quality.","PeriodicalId":104202,"journal":{"name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","volume":"52 2S2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127995718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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