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"The present book discusses the three fields, fuzzy systems, rough sets and ensemble techniques. As the trained ensemble should represent a single hypothesis, a lot of attention is placed on the possibility to combine fuzzy rules from fuzzy systems being members of classification ensemble. Furthermore, an emphasis is placed on ensembles that can work on incomplete data, thanks to rough set theory."

"ABSTRAKRancangan suatu Sistem Instrumentasi Penyimpul Fuzzy (SIPF) digital 64 bit untuk mengolah algoritma penyimpul fuzzy (Fuzzy Inference). Suatu sistem fuzzy yang terdiri dari SIPF dan mikroprosesor 32 bit memiliki kecepatan proses penyimpulan lebih tinggi bila dibandingkan dengan sistem yang hanya mengimplementasi perangkat lunak saja.. SIPF hanya digunakan untuk mengambil kesimpulan, sementara proses fuzzifikasi serta defuzzifikasi dilakukan oleh mikroprosesor sendiri yang juga mengendalikan SIPF. Disamping SIPF, algoritma penyimpulan yang teroptimasi juga dapat meningkatkan akselerasi pengkalkulasian aturan dasar (rule base).Pada Skripsi ini dilakukan perancangan serta peralcitan Sistem Instrumentasi Penyimpul Fuzzy, dengan menggunakan komponen-komponen murah dan sederhana serta mudah didapat. Hasil utama yang didapat adalah suatu rancangan dari sistem instrumentasi yang berfungsi sebagai alat bantu kalkulasi aturan fuzzy paralel yang kerjanya dikendalikan oleh mikroprosesor induk."

"The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving.The book is organised as follows : Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fuzzy relations and fuzzy rules. Chapter 8 presents a method for extracting fuzzy relations from data. All the algorithms presented in Chapters 2-8 are validated by computer experiments and illustrated by solving medical and technical forecasting and diagnosis problems. Finally, Chapter 9 includes applications of the proposed methodology in dynamic and inventory control systems, prediction of results of football games, decision making in road accident investigations, project management and reliability analysis. "

"Salah satu masalah yang dihadapi dalam Supply Chain Management adalah pencarian jalur. Jalur terbaik tidak hanya tergantung pada jarak, tetapi juga variabel lain, seperti: kualitas perusahaan yang terlibat, kualitas produk yang dikirimkan, dan nilai lain yang dipengaruhi oleh pengukuran kualitas. Umumnya, Ant Colony Optimization bisa mencari jalur terbaik yang hanya memiliki satu jalur objektif. Tapi akan sulit untuk diadopsi, karena dalam kasus nyata, jalur supply memiliki banyak jalur dan tujuan (khususnya pasokan minyak kelapa sawit berbasis bioenergi). Tujuan dari penelitian ini adalah untuk meningkatkan Ant Colony Optimization dalam menyelesaikan masalah jalur supply dengan menggunakan Fuzzy Ant Colony Optimization. Tujuan pengembangan Fuzzy Ant Colony Optimization dijelaskan disini, yaitu digunakan untuk mencari jalur supply terbaik.

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AbstractOne of problem faced in supply chain management is path searching. The best path depend not only on distance, but also other variables, such as: the quality of involved companies, quality of delivered product, and other value resulted by quality measurement. Commonly, the ant colony optimization could search the best path that has only one objective path. But it would be difficult to be adopted, because in the real case, the supply path has multi path and objectives (especially in palm oil based bioenergy supply). The objective of this paper is to improve the ant colony optimization for solving multi objectives based supply path problem by using fuzzy ant colony optimization. The developed multi objectives fuzzy ant colony optimization design was explained here, that it was used to search the best supply path."

"ABSTRACTNational governments rely on global performance indicators tomeasure where they stand and to build future strategies. However, no previousstudy has compiled various indices to investigate pathways to governmentperformance. We use fuzzy set analysis to investigate what role each of fivedeterminants of government performance trait competitiveness, change orientedcitizenship behavior, public service motivation, organizational identification,and corruption tolerance play in three representative government performanceindicators Government Effectiveness, Government Efficiency, andThroughput. The results indicate that government performance as measuredby these three indicators is commonly tied to strongly public service motivatedemployees. These three indicators are distinguished from one another withregard to the number of factors that contribute to the construction of sufficientconfigurations, the role of innovation inclined factors, and the role of corruptiontolerance."