Development of Fuzzy Inference System for Automatic Tea Making

被引：0

作者：

Ahamed, Nizam Uddin ^{[1
]}

Bin Taha, Zahari ^{[1
]}

Khairuddin, Ismail B. Mohd ^{[1
]}

Rabbi, Mohammad Fazle ^{[2
]}

Sikandar, Tasriva ^{[2
]}

Palaniappan, Rajkumar ^{[3
]}

Ali, Md. Asraf ^{[4
]}

Rahman, S. A. M. Matiur ^{[4
]}

Sundaraj, K. ^{[5
]}

机构：

[1] Univ Malaysia Pahang, Fac Mfg Engn, iMAMS Lab, Pekan 26600, Malaysia

[2] Univ Malaysia Pahang, Fac Elect & Elect Engn, Pekan 26600, Malaysia

[3] VIT Univ, Sch Elect Engn, Vellore, Tamil Nadu, India

[4] Daffodil Int Univ, Dhaka, Bangladesh

[5] Univ Tekn Malaysia Melaka, Fac Elect & Comp Engn, Durian Tunggal, Melaka, Malaysia

来源：

2016 IEEE INTERNATIONAL CONFERENCE ON AUTOMATIC CONTROL AND INTELLIGENT SYSTEMS (I2CACIS) | 2016年

关键词：

Fuzzy inference system; tea grading; automatic tea maker;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a fuzzy inference system has been developed for automatic tea making process. The system takes five inputs and gives two output which determines the grade of black tea and milk tea. Specifically, the proposed system considers five important characteristics of hot tea beverage such as water temperature, sugar, milk, brewing time and tea leaves quantity for grading the standard of the drink according to the consumer's requirement. Both black tea and milk tea can be rated with a grade based on the human expert judgment which is according to the taste and aroma of the tea. This automatic tea making system can let the users choose their preferred type of tea without figuring out the complicated process to making a cup of hot tea beverage.

引用

页码：196 / 201

页数：6

共 50 条

[31] Automatic Synthesis of Fuzzy Inference Systems for Classification
Paredes, Jorge
Tanscheit, Ricardo
Vellasco, Marley
Koshiyama, Adriano
INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS, IPMU 2016, PT I, 2016, 610 : 486 - 497
[32] Multi Criteria Decision Making using Fuzzy Inference System : A Case in Manufacturing
Vasudevan, Hari
Deshpande, Naresh C.
Rajguru, Ramesh R.
2014 INTERNATIONAL CONFERENCE ON CONTROL, INSTRUMENTATION, COMMUNICATION AND COMPUTATIONAL TECHNOLOGIES (ICCICCT), 2014, : 1280 - 1286
[33] Comparative Analysis of Membership Function on Mamdani Fuzzy Inference System for Decision Making
Harliana, Putri
Rahim, Robbi
INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY (ICONICT), 2017, 930
[34] Automatic fuzzy decision making system with learning for competing and connected businesses
Oderanti, Festus Oluseyi
De Wilde, Philippe
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (12) : 14574 - 14584
[35] Inference and decision making with fuzzy cognitive structures
Juliano, BA
IC-AI'2000: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 1-III, 2000, : 405 - 411
[36] Automatic Impedance Matching Method With Adaptive Network Based Fuzzy Inference System for WPT
Li, Yang
Dong, Weihao
Yang, Qingxin
Jiang, Shan
Ni, Xin
Liu, Jiaming
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2020, 16 (02) : 1076 - 1085
[37] Automatic Moving Vehicle Detection and Classification Based on Artificial Neural Fuzzy Inference System
Murugan, V.
Vijaykumar, V. R.
WIRELESS PERSONAL COMMUNICATIONS, 2018, 100 (03) : 745 - 766
[38] Fractional Fuzzy Inference System: The New Generation of Fuzzy Inference Systems
Mazandarani, Mehran
Li, Xiu
IEEE ACCESS, 2020, 8 : 126066 - 126082
[39] LDG AUTOMATIC FLOW-RATE CONTROL FOR ENERGY SYSTEM USING FUZZY INFERENCE
HUKUOKA, K
TETSU TO HAGANE-JOURNAL OF THE IRON AND STEEL INSTITUTE OF JAPAN, 1986, 72 (12): : 1131 - 1131
[40] Roadway Gate Automatic Control System with the use of Fuzzy Inference and Computer Vision Technologies
Amosov, O. S.
Baena, S. G.
Ivanov, Y. S.
Htike, Soe
PROCEEDINGS OF THE 2017 12TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2017, : 706 - 711

← 1 2 3 4 5 →