Fuzzy Systems Software: Taxonomy, Current Research Trends and Prospects

2011 (32 papers)

  • Abdelgawad, M.; Fayek, A.R. Fuzzy Reliability Analyzer: Quantitative Assessment of Risk Events in the Construction Industry Using Fuzzy Fault-Tree Analysis. Journal of Construction Engineering and Management 137:4 (2011) 294–302. Doi:10.1061/(ASCE)CO.1943-7862.0000285
  • Alcala-Fdez, J.; Fernandez, A.; Luengo, J.; Derrac, J.; Garcia, S.; Sanchez, L.; Herrera, F. KEEL data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework. Journal of Mult.-Valued Logic and Soft Computing 17 (2011) 255-287.
  • Aljahdali, S.; Sheta, A. Predicting the Reliability of Software Systems Using Fuzzy Logic. International Conference on Information Technology: New Generations (ITNG 2011), Las Vegas (USA), pp. 36-40, 11-13 April, 2011.
  • Almendros-Jiménez, J.M.; Luna, A.; Moreno, G. A Flexible XPath-Based Query Language Implemented with Fuzzy Logic Programming. In: Rule-Based Reasoning, Programming, and Applications (Ed. Bassiliades, N.; Governatori, G.; Paschke, A.). Lecture Notes in Computer Science 6826, Springer, pp. 186–193, 2011. Doi:10.1007/978-3-642-22546-8
  • Alonso, J.M.; Magdalena, L. Generating understandable and accurate fuzzy rule-based systems in a java environment. In: International Workshop on Fuzzy Logic and Applications (Ed. Fanelli, A.M.; Pedrycz, W.; Petrosino, A.). Lecture Notes in Artificial Intelligence 6857, Springer-Verlag Berlin Heidelberg, pp. 212–219, 2011. Doi:10.1007/978-3-642-23713-3_27
  • Attarzadeh, I.; Ow, S.H. Improving estimation accuracy of the COCOMO II using an adaptive fuzzy logic model. IEEE International Conference on Fuzzy Systems (2011) 2458-2464. Doi: 10.1109/FUZZY.2011.6007471
  • Azzeh, M.; Neagu, D.; Cowling, P.I. Analogy-based software effort estimation using fuzzy numbers. Journal of Systems and Software 84:2 (2011) 270-284. Doi:10.1016/j.jss.2010.09.028
  • Cheng, C.-H.; Chang, J.-R.; Kuo, C.-Y. A CMMI appraisal support system based on a fuzzy quantitative benchmarks model. Expert Systems with Applications 38:4 (2011) 4550-4558. Doi:10.1016/j.eswa.2010.09.129
  • Cooper, B.; Glaesser, J. Paradoxes and pitfalls in using fuzzy set QCA: Illustrations from a critical review of a study of educational inequality. Sociological Research Online 16:3 (2011) Article Number: 8. Doi:10.5153/sro.2444
  • Cooper, B.; Glaesser, J. Using case-based approaches to analyse large datasets: a comparison of Ragin's fsQCA and fuzzy cluster analysis. International Journal of Social Research Methodology 14:1 (2011) 31–48. Doi:10.1080/13645579.2010.483079
  • El-Sebakhy, E.A. Functional networks as a novel data mining paradigm in forecasting software development efforts. Expert Systems with Applications 38:3 (2011) 2187-2194. Doi:10.1016/j.eswa.2010.08.005
  • Gil-Sanchez, L.; Garcia-Breijo, E.; Garrigues, J.; Alcaniz, M.; Escriche, I.; Kadar, M. Classification of honeys of different floral origins by artificial neural networks. IEEE Conference on Sensors (2011) 1780-1783. Doi:10.1109/ICSENS.2011.6127058
  • Guillaume, S.; Charnomordic, B. Learning interpretable fuzzy inference systems with FisPro. Information Sciences 181:20 (2011) 4409-4427. Doi:10.1016/j.ins.2011.03.025
  • He, J.H.; Bai, X.; Lin, Q.; Xiong, D. A fuzzy-ECM approach to estimate software project schedule under uncertainties. 9th IEEE International Symposium on Parallel and Distributed Processing with Applications Workshops (2011) 316-321. Doi:10.1109/ISPAW.2011.33
  • Kok, K.; van Vliet, M. Using a participatory scenario development toolbox: Added values and impact on quality of scenarios. Journal of Water and Climate Change 2:2-3 (2011) 87-105. Doi:10.2166/wcc.2011.032
  • Kong, C.; Koo, Y. GUI type fault diagnostic program for a turboshaft engine using fuzzy and neural networks. International Journal of Turbo and Jet-engines 28:1 (2011) 31-39. Doi:10.1515/TJJ.2011.003
  • Lazzerini, B.; Mkrtchyan, L. Analyzing risk impact factors using extended fuzzy cognitive maps. IEEE Systems Journal 5:2 (2011) 288-297. Doi:10.1109/JSYST.2011.2134730
  • Lee, J.; dos Santos, W.P. An adaptive fuzzy-based system to simulate, quantify and compensate color blindness. Integrated Computer-aided Engineering 18:1 (2011) 29-40. Doi:10.3233/ICA-2011-0356
  • Lerthathairat, P.; Prompoon, N. An Approach for Source Code Classification Using Software Metrics and Fuzzy Logic to Improve Code Quality with Refactoring Techniques. In: Software Engineering and Computer Systems (Ed. Zain, J.M.), Springer-Verlag Berlin / Heidelberg, pp. 478-492), 2011.
  • Lopez-Martin, C. A fuzzy logic model for predicting the development effort of short scale programs based upon two independent variables. Applied Soft Computing 11:1 (2011) 724-732. Doi:10.1016/j.asoc.2009.12.034
  • Mendes, J.; Araujo, R.; Sousa, P.; Apostolo, F.; Alves, L. An architecture for adaptive fuzzy control in industrial environments. Computers in Industry 62:3 (2011) 364-373. Doi:10.1016/j.compind.2010.11.001
  • Messina, A.; Langer, H. Pattern recognition of volcanic tremor data on Mt. Etna (Italy) with KKAnalysis-A software program for unsupervised classification. Computers and Geosciences 37:7 (2011) 953-961. Doi:10.1016/j.cageo.2011.03.015
  • Munoz-Hernandez, S.; Pablos-Ceruelo, V.; Strass, H. RFuzzy: Syntax, semantics and implementation details of a simple and expressive fuzzy tool over Prolog. Information Sciences 181:10 (2011) 1951–1970. Doi:10.1016/j.ins.2010.07.033
  • Pablos-Ceruelo, V.; Munoz-Hernandez, S. Introducing priorities in Rfuzzy?: Syntax And Semantics. International Conference on Mathematical Methods in Science and Engineering (CMMSE 2011), Benidorm (Spain), pp. 918-929, 26-30 June, 2011.
  • Pedoia, V.; Colli, V.; Strocchi, S.; Vite, C.; Binaghi, E.; Conte, L. fMRI analysis software tools: An evaluation framework. Conference on Medical Imaging - Biomedical Applications in Molecular, Structural, and Functional Imaging 7965 (2011) Article Number: 796528. Doi:10.1117/12.877067
  • Rowhanimanesh, A.; Akbarzadeh-T, M.R. Perception-based heuristic granular search: Exploiting uncertainty for analysis of certain functions. Scientia Iranica 18:3 (2011) 617-626. Doi:10.1016/j.scient.2011.04.015
  • Tanase, C.; Caramihai, M.; Ungureanu, C.; Sarbu, G.; Chirvase, A.A.; Muntean, O. Software application for intelligent control of a bioprocess. Case study. 21st European Symposium on Computer Aided Process Engineering, Book Series: Computer-Aided Chemical Engineering 29 (2011) 643-647. Doi:10.1016/B978-0-444-53711-9.50129-2
  • Wagner, C.; Miller, S.; Garibaldi, J.M. A Fuzzy Toolbox for the R Programming Language. IEEE International Conference On Fuzzy Systems (2011) 1185–1192. Doi:10.1109/FUZZY.2011.6007743
  • Wali, W.A.; Hassan, K. H.; Cullen, J.D.; Al-Shamma'a, A.I.; Shaw, A.; Wylie, S.R. Artificial intelligent control for a novel advanced microwave biodiesel reactor. 16th Conference in the Biennial Sensors and their Applications, Book Series: Journal of Physics Conference Series 307 (2011). Doi:10.1088/1742-6596/307/1/012042
  • Wieland, R.; Mirschel, W.; Groth, K.; Pechenick, A.; Fukuda, K. A new method for semi-automatic fuzzy training and its application in environmental modeling. Environmental Modelling and Software 26:12 (2011) 1568-1573. Doi:10.1016/j.envsoft.2011.07.017
  • Yuen, K.K.F.; Lau, Henry C.W. A fuzzy group analytical hierarchy process approach for software quality assurance management: Fuzzy logarithmic least squares method. Expert Systems with Applications 38:8 (2011) 10292-10302. Doi:10.1016/j.eswa.2011.02.057
  • Zhang, M.; Adamu, B.; Lin, C.C.; Yang, P. Gene expression analysis with integrated fuzzy C-means and pathway analysis. 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2011) 936-939. Doi:10.1109/IEMBS.2011.6090211