scholarly journals A Cloud Trust Evaluation System Using Hierarchical Fuzzy Inference System for Service Selection

2014 ◽  
Author(s):  
Chenhao Qu ◽  
Rajkumar Buyya
Keyword(s):  
Fuzzy Inference System ◽  
Evaluation System ◽  
Fuzzy Inference ◽  
Service Selection ◽  
Trust Evaluation ◽  
Inference System

Study a Fuzzy Inference System on the Supplier Evaluation in E-Manufacturing

2009 ◽  
Vol 16-19 ◽  
pp. 189-192 ◽  
Author(s):  
Jian Chen ◽  
Ming Hong Wu ◽  
Wen Rong Jiang ◽  
An Bao Wang ◽  
Ji Hong Yan
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Fuzzy Inference System ◽  
Evaluation System ◽  
Supplier Selection ◽  
Fuzzy Inference ◽  
Supplier Evaluation ◽  
Inference System ◽  
Key Factor

The supplier selection and evaluation is a key factor of the intelligent supplier selection & evaluation system in e-manufacturing. The model used for supplier selection is Fuzzy inference system which is introduced in the paper. The paper started with the brief introduction of the intelligent internet supplier selection & evaluation system. It concentrated to introduce the application of the fuzzy set model for supplier selection. This paper will introduce the design of the fuzzy sets model, and the evaluation results.

scholarly journals Diagnosis Penyakit Jantung Menggunakan Adaptive Neuro-Fuzzy Inference System (ANFIS)

MATICS ◽  
2016 ◽  
Vol 8 (2) ◽  
pp. 81
Author(s):  
Khadijah Fahmi Hayati Holle
Keyword(s):  
Heart Disease ◽  
Computer Technology ◽  
Fuzzy Inference System ◽  
Evaluation System ◽  
Fuzzy Inference ◽  
Inference System ◽  
System Diagnosis ◽  
Neuro Fuzzy ◽  
Output System ◽  
Health Field

The number of uncertain risk factor in heart disease makes experts difficult to diagnose its disease. Computer technology in the health field is mostly used. In this paper, we implement a system to diagnose heart disease. The used method is Adaptive neuro-fuzzy inference system which combine the advantage of fuzzy and neural network. The used data is UCI Cleveland data that have 13 attributes as inputs. Output system diagnosis compared with observational data for evaluation. System performance tested by calculating accuracy. Tests were also conducted on the variation of the learning rate, iteration, minimum error, and the use of membership functions. Accuracy obtained from test is 65,657% where using membership function Beta.

User-centric framework to facilitate trust worthy cloud service provider selection based on fuzzy inference system

2021 ◽  
pp. 1-9
Author(s):  
M. Sujatha ◽  
K. Geetha ◽  
P. Balakrishnan
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Service Providers ◽  
Selection Process ◽  
Cost Model ◽  
Service Selection ◽  
Cloud Service ◽  
Second Phase ◽  
Inference System ◽  
The Cost

The widespread adoption of cloud computing by several companies across diverse verticals of different sizes has led to an exponential growth of Cloud Service Providers (CSP). Multiple CSPs offer homogeneous services with a vast array of options and different pricing policies, making the suitable service selection process complex. Our proposed model simplifies the IaaS selection process that can be used by all users including clients from the non-IT background. In the first phase, requirements are gathered using a simple questionnaire and are mapped with the compute services among different alternatives.In the second phase, we have implemented the Sugeno Fuzzy inference system to rank the service providers based on the QoS attributes to ascertain the appropriate selection. In the third phase, we have applied the cost model to identify the optimal CSP. This framework is validated by applying it for a gaming application use case and it has outperformed the online tools thus making it an exemplary model.

Aplikasi Peramalan Kebutuhan Beban Listrik Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS)

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

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.

ZERO-DAY POLYMORPHIC CYBERATTACKS DETECTION USING FUZZY INFERENCE SYSTEM

2020 ◽  
pp. 8-13
Author(s):  
V. V. Fesokha ◽  
I. Y. Subach ◽  
V. O. Kubrak ◽  
A. V. Mykytiuk ◽  
S. O. Korotaiev
Keyword(s):  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System
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