A fuzzy inference automatic negotiation system with bayesian learning

Author(s):  
Wu Yuying ◽  
Li Jiyuan ◽  
Yan Feng
2019 ◽  
Author(s):  
Shinichi Nakajima ◽  
Kazuho Watanabe ◽  
Masashi Sugiyama

2016 ◽  
pp. 141-149
Author(s):  
S.V. Yershov ◽  
◽  
R.М. Ponomarenko ◽  

Parallel tiered and dynamic models of the fuzzy inference in expert-diagnostic software systems are considered, which knowledge bases are based on fuzzy rules. Tiered parallel and dynamic fuzzy inference procedures are developed that allow speed up of computations in the software system for evaluating the quality of scientific papers. Evaluations of the effectiveness of parallel tiered and dynamic schemes of computations are constructed with complex dependency graph between blocks of fuzzy Takagi – Sugeno rules. Comparative characteristic of the efficacy of parallel-stacked and dynamic models is carried out.


2017 ◽  
Vol 3 (1) ◽  
pp. 36-48
Author(s):  
Erwan Ahmad Ardiansyah ◽  
Rina Mardiati ◽  
Afaf Fadhil

Prakiraan atau peramalan beban listrik dibutuhkan dalam menentukan jumlah listrik yang dihasilkan. Ini menentukan  agar tidak terjadi beban berlebih yang menyebabkan pemborosan atau kekurangan beban listrik yang mengakibatkan krisis listrik di konsumen. Oleh karena itu di butuhkan prakiraan atau peramalan yang tepat untuk menghasilkan energi listrik. Teknologi softcomputing dapat digunakan  sebagai metode alternatif untuk prediksi beban litrik jangka pendek salah satunya dengan metode  Adaptive Neuro Fuzzy Inference System pada penelitian tugas akhir ini. Data yang di dapat untuk mendukung penelitian ini adalah data dari APD PLN JAWA BARAT yang berisikan laporan data beban puncak bulanan penyulang area gardu induk majalaya dari januari 2011 sampai desember 2014 sebagai data acuan dan data aktual januari-desember 2015. Data kemudian dilatih menggunakan metode ANFIS pada software MATLAB versi b2010. Dari data hasil pelatihan data ANFIS kemudian dilakukan perbandingan dengan data aktual dan data metode regresi meliputi perbandingan anfis-aktual, regresi-aktual dan perbandingan anfis-regresi-aktual. Dari perbandingan disimpulkan bahwa data metode anfis lebih mendekati data aktual dengan rata-rata 1,4%, menunjukan prediksi ANFIS dapat menjadi referensi untuk peramalan beban listrik dimasa depan.


2016 ◽  
Vol E99.B (12) ◽  
pp. 2614-2622 ◽  
Author(s):  
Kai ZHANG ◽  
Hongyi YU ◽  
Yunpeng HU ◽  
Zhixiang SHEN ◽  
Siyu TAO

Author(s):  
Hirosato SEKI ◽  
Fuhito MIZUGUCHI ◽  
Satoshi WATANABE ◽  
Hiroaki ISHII ◽  
Masaharu MIZUMOTO

2009 ◽  
Vol 8 (3) ◽  
pp. 887-897
Author(s):  
Vishal Paika ◽  
Er. Pankaj Bhambri

The face is the feature which distinguishes a person. Facial appearance is vital for human recognition. It has certain features like forehead, skin, eyes, ears, nose, cheeks, mouth, lip, teeth etc which helps us, humans, to recognize a particular face from millions of faces even after a large span of time and despite large changes in their appearance due to ageing, expression, viewing conditions and distractions such as disfigurement of face, scars, beard or hair style. A face is not merely a set of facial features but is rather but is rather something meaningful in its form.In this paper, depending on the various facial features, a system is designed to recognize them. To reveal the outline of the face, eyes, ears, nose, teeth etc different edge detection techniques have been used. These features are extracted in the term of distance between important feature points. The feature set obtained is then normalized and are feed to artificial neural networks so as to train them for reorganization of facial images.


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