scholarly journals Research on Multiple Authentication Fuzzy Logic Relationship

2018 ◽  
Author(s):  
Yuanyuan Wang ◽  
Guojian Cheng
Keyword(s):  
Fuzzy Logic ◽  
Logic Relationship

scholarly journals FORECASTING JUMLAH MAHASISWA BARU MENGGUNAKAN METODE AUTOMATIC CLUSTERING AND FUZZY LOGIC RELATIONSHIP MARKOV CHAIN (STUDI KASUS : FAKULTAS TEKNOLOGI INFORMASI DAN KOMUNIKASI VISUAL INSTITUT SAINS DAN TEKNOLOGI AL-KAMAL)

2022 ◽  
Vol 4 (1) ◽  
pp. 289-293
Author(s):  
Mundirin Mundirin
Keyword(s):  
Fuzzy Logic ◽  
Markov Chain ◽  
Communication Technology ◽  
Visual Communication ◽  
Science And Technology ◽  
Secondary Data ◽  
Automatic Clustering ◽  
New Students ◽  
Academic Year ◽  
Logic Relationship

Abstraction                     Forecasting or forecasting is a calculation analysis technique that is done by carrying out qualitative and quantitative approaches to think about future events using reference data in the past. The purpose of this study is to predict the number of new students at the Faculty of Information and Visual Communication Technology at the Al-Kamal Institute of Science and Technology in the academic year 2020/2021. Prediction of the number of new students in the Faculty of Information and Visual Communication Technology of the Al-Kamal Institute of Science in the future accurately is very important to do, because many decisions can be taken by the Leaders of the Al-Kamal Institute of Science and Technology from these predictions. Markov Chain Automatic Clustering and Fuzzy Logic Relationship Method was chosen because it has a better level of accuracy among other Fuzzy Logic methods. The data used in this study are secondary data obtained from the Academic Information System of the Al-Kamal Institute of Science and Technology. Based on this research it was found that the predicted results of the number of new students of the Faculty of Information and Visual Communication Technology at the Al-Kamal Institute of Science and Technology in the academic year 2020/2021 amounted to 64 with a MAPE of 8.25%

scholarly journals Implementasi Metode Fuzzy Time Series untuk Peramalan Jumlah Pengunjung di Benteng Fort Rotterdam

2020 ◽  
Vol 2 (1) ◽  
pp. 1
Author(s):  
V. Vivianti ◽  
Muhammad Kasim Aidid ◽  
Muhammad Nusrang
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Fuzzy Time Series ◽  
Logical Relationship ◽  
Logic Relationship ◽  
Fuzzy Logical

Abstract, Peramalan merupakan kegiatan yang dilakukan untuk memprediksi nilai suatu variable di waktu yang akan datang. Tujuan dari penelitian ini adalah mengimplementasikan Metode Fuzzy Time Series untuk memprediksi jumlah Pengunjung Benteng Fort Rotterdam. Metode Fuzzy Time Series adalah sebuah metode peramalan yang menggunakan himpunan Fuzzy sebagai dasar dalam Proses prediksi. Tahapan Peramalan dalam penelitian ini adalah mendefinisikan semesta pembicaraan U, menentukan jumlah dan Panjang kelas interval, defuzzifikasi dan mendefenisikan himpunan Fuzzy pada U, melakukan Fuzzifikasi pada data jumlah pengunjung, menentukan Fuzzy logic relationship (FLR), membentuk Fuzzy Logical Relationship Group (FLRG), melakukan defuzzifikasi, dan melakukan perhitungan peramalan. Dalam meramalkan jumlah Pengunjung di Benteng Fort Rotterdam dengan menggunakan Metode Fuzzy Time Series diperoleh hasil peramalan sebanyak 16240,35 atau dibulatkan menjadi 16240 Pengunjung pada bulan selanjutnya, dengan nilai MAPE sebesar 119,93 dan RMSE sebesar 4739,08.Keywords: Fuzzy, Time Series, Peramalan, Fort Rotterdam

scholarly journals Peramalan Harga Emas Menggunakan Metode Average Based And Fuzzy Logic Relationship

2021 ◽  
Vol 18 (2) ◽  
pp. 230-242
Author(s):  
A M Pratiwi ◽  
S Musdalifah ◽  
D Lusiyanti
Keyword(s):  
Fuzzy Logic ◽  
Mean Absolute Percentage Error ◽  
Percentage Error ◽  
Absolute Percentage Error ◽  
Logic Relationship

Emas merupakan alternatif yang cenderung dipilih kebanyakan orang untuk berinvestasi karena beberapa alasan, salah satunya menguntungkan. Untuk memperoleh keuntungan yang optimal, pelaku investasi harus mengetahui pergerakan harga emas sehingga pelaku investasi tahu kapan harus membeli emas dan kapan harus menjual emas. Pergerakan harga emas dapat dipantau dengan peramalan. Metode peramalan yang digunakan dalam penelitian ini adalah average based and fuzzy logic relationship yang merupakan salah satu metode dengan konsep fuzzy logic. Metode tersebut memberikan tingkat akurasi yang dihitung menggunakan MAPE (Mean Absolute Percentage Error) sebesar  Hasil penelitian menunjukkan bahwa peramalan pergerakan harga emas pada bulan Oktober 2020  Desember 2021 dalam rentang harga dengan harga emas tertinggi terjadi pada bulan Desember 2020.

Hysteresis in Categorization: Fuzzy Logic Makes Fuzzy Boundaries

2012 ◽  
Author(s):  
Thomas M. Crawford ◽  
Justin Fine ◽  
Donald Homa
Keyword(s):  
Fuzzy Logic

Continuous Estimation of CO2 Production during Exercise

1997 ◽  
Vol 36 (04/05) ◽  
pp. 368-371
Author(s):  
R. Soma ◽  
Y. Yamamoto
Keyword(s):  
Fuzzy Logic ◽  
Steady State ◽  
Infusion Rate ◽  
Feedback System ◽  
Whole Body ◽  
Co2 Production ◽  
Cycle Exercise ◽  
Continuous Estimation ◽  
Breath Measurement ◽  
13Co2 Enrichment

Abstract.A new method was developed for continuous isotopic estimation of human whole body CO2 rate of appearance (Ra) during non-steady state exercise. The technique consisted of a breath-by-breath measurement of 13CO2 enrichment (E) and a real-time fuzzy logic feedback system which controlled NaH13CO3 infusion rate to achieve an isotopic steady state. Ra was estimated from the isotope infusion rate and body 13CO2 enrichment which was equal to E at the isotopic steady state. During a non-steady state incremental cycle exercise (5 w/min or 10 w/min), NaH13CO3 infusion rate was successfully increased by the action of feedback controller so as to keep E constant.

Modified fuzzy-based greedy routing protocol for VANETs

2020 ◽  
Vol 39 (6) ◽  
pp. 8357-8364
Author(s):  
Thompson Stephan ◽  
Ananthnarayan Rajappa ◽  
K.S. Sendhil Kumar ◽  
Shivang Gupta ◽  
Achyut Shankar ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Routing Protocol ◽  
Intelligent Transportation Systems ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Research Area ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Greedy Routing ◽  
Hoc Networks

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

Design and Simulation of Smart Control System for Internet Traffic Distribution on Servers by Using Fuzzy Logic System

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Raid Daoud ◽  
Yaareb Al-Khashab
Keyword(s):  
Fuzzy Logic ◽  
Control System ◽  
Input Parameter ◽  
Traffic Density ◽  
The Internet ◽  
Linguistic Variables ◽  
Internet Service ◽  
Traffic Distribution ◽  
Smart Control ◽  
High Level

The internet service is provided by a given number of servers located in the main node of internet service provider (ISP). In some cases; the overload problem was occurred because a demand on a given website goes to very high level. In this paper, a fuzzy logic control (FLC) has proposed to distribute the load into the internet servers by a smart and flexible manner. Three effected parameters are tacked into account as input for FLC: link capacity which has three linguistic variables with Gaussian membership function (MF): (small, medium and big), traffic density with linguistic variables (low, normal and high) and channel latency with linguistic variables (empty, half and full); with one output which is the share server status (single, simple and share). The proposed work has been simulated by using MATLAB 2016a, by building a structure in the Fuzzy toolbox. The results were fixed by two manners: the graphical curves and the numerical tables, the surface response was smoothly changed and translates the well-fixed control system. The numerical results of the control system satisfy the idea of the smart rout for the incoming traffics from the users to internet servers. So, the response of the proposed system for the share of server ratio is 0.122, when the input parameter in the smallest levels; and the ratio is 0.879 when the input parameters are in highest level. The smart work and flexible use for the FLC is the main success solution for most of today systems control.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

FUZZY LOGIC APPLICATION IN TRANSPOTATION PROBLEMS

2013 ◽  
Author(s):  
Dieu Thi Xuan Duong ◽  
◽  
Veeris Ammarapala
Keyword(s):  
Fuzzy Logic
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