http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Recent advances on soft computing and data mining
the second International Conference on Soft Computing and Data Mining (SCDM-2016), Bandung, Indonesia, August 18-20, 2016 Proceedings
International Conference on Soft Computing and Data Mining 2016 : Bandung, Indonesia)
This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th?20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.
Preface; Conference Organization; Patron; Honorary Chairs; Steering Committee; General Chairs; Organizing Committee; Program Committee Chairs; Proceeding Chairs; Workshop Chairs; Sponsorship; Program Committee ; Soft Computing; Data Mining; Workshop on Ensemble Methods and Their Applications; Workshop on Web Mining, Services and Security; Contents; Soft Computing; Cluster Validation Analysis on Attribute Relative of Soft-Set Theory; 1 Introduction; 2 Preliminaries; 2.1 Soft-Set Theory; 2.2 Clustering Attribute Selection; 2.3 Cluster Validation Method; 3 Attribute Relative of Soft-Set Theory
4 Result and Discussion5 Conclusions; References; Optimizing Weights in Elman Recurrent Neural Networks with Wolf Search Algorithm; Abstract; 1 Introduction; 2 Wolf Search (WS) Algorithm; 2.1 The Proposed WRNN Algorithm; 3 Results and Discussion; 3.1 Preliminary Study; 3.2 Classification Datasets; 4 Conclusion; Acknowledgments; References; Optimization of ANFIS Using Artificial Bee Colony Algorithm for Classification of Malaysian SMEs; 1 Introduction; 2 The ANFIS Concept; 3 Artificial Bee Colony Algorithm; 4 Methodology; 4.1 ANFIS Rule-Base Minimization and Accuracy Maximization Using ABC
5 Simulation Results and Analysis6 Conclusion; References; Forecasting of Malaysian Oil Production and Oil Consumption Using Fuzzy Time Series; Abstract; 1 Introduction; 2 The Basic Theories of FTS and RTS; 2.1 FTS Theory and Its Procedure; 2.2 RTS Theory and Its Procedure; 3 Proposed Interval Adjustment and Algorithm in FTS; 4 Empirical Analysis; 5 Conclusion; Acknowledgment; References; A Fuzzy TOPSIS with Z-Numbers Approach for Evaluation on Accident at the Construction Site; Abstract; 1 Introduction; 2 The Steps of Z-Numbers with Fuzzy TOPSIS; 3 An Application; 4 Comparative Studies
5 ConclusionReferences; Formation Control Optimization for Odor Localization; Abstract; 1 Introduction; 2 Odor Localization Design; 2.1 Odor Localization Process; 2.2 The Localization Process-Based FKN-PSO Algorithm; 3 Experimental Results; 4 Conclusion and Future Work; Acknowledgments; References; A New Search Direction for Broyden's Family Method in Solving Unconstrained Optimization Problems; Abstract; 1 Introduction; 2 Preliminaries; 3 Proposed Model; 4 Experimental Result; 5 Conclusion; References
Improved Functional Link Neural Network Learning Using Modified Bee-Firefly Algorithm for Classification TaskAbstract; 1 Introduction; 2 Functional Link Neural Network Learning Scheme; 3 Modified Artificial Bee Colony; 4 Firefly Algorithm; 5 Modified Bee-Firefly Algorithm; 6 Experimentation and Result; 7 Conclusion; Acknowledgments; References; Artificial Neural Network with Hyperbolic Tangent Activation Function to Improve the Accuracy of COCOMO II Model; Abstract; 1 Introduction; 2 Related Works; 3 Rudimentary; 3.1 COCOMO II Model; 3.2 Artificial Neural Network; 3.2.1 Identity Function
Tutut Herawan, Rozaida Ghazali, Nazri Mohd Nawi, Mustafa Mat Deris, editors.
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Advances in intelligent systems and computing ; 549