Predicting the individual best saddle height of bicycle based on electromyography and Fuzzy Inference

2009 ◽  
Author(s):  
Tatsushi Tokuyasu ◽  
Hiroki Taniguchi ◽  
Shimpei Matsumoto ◽  
Keichi Ohba
Keyword(s):  
Fuzzy Inference ◽  
The Individual

Estimation of Chlorophyll Concentration Index at Leaves using Artificial Neural Networks

2016 ◽  
Vol 26 (02) ◽  
pp. 1750026 ◽  
Author(s):  
Mehmet Serhat Odabas ◽  
Nurettin Senyer ◽  
Gokhan Kayhan ◽  
Erhan Ergun
Keyword(s):  
Fuzzy Inference ◽  
Chlorophyll Concentration ◽  
Echinacea Purpurea ◽  
General Regression Neural Network ◽  
Medicinal And Aromatic Plants ◽  
Inference System ◽  
Spad Value ◽  
Neuro Fuzzy ◽  
The Individual ◽  
General Regression

In this study, the effectiveness of an SPAD-502 portable chlorophyll (Chl) meter was evaluated for estimating the Chl contents in leaves of some medicinal and aromatic plants. To predict the individual chlorophyll concentration indexes of St. John’s wort (Hypericum perforatum L.), mint (Mentha angustifolia L.), melissa (Melissa officinalis L.), thyme (Thymus sp.), and echinacea (Echinacea purpurea L.), models were developed using SPAD value. Multi-layer perceptron (MLP), adaptive neuro fuzzy inference system (ANFIS), and general regression neural network (GRNN) were used for determining the chlorophyll concentration indexes.

Vehicles Dispatching Problem for Cooperative Deliveries from Multiple Depots

2000 ◽  
Vol 4 (2) ◽  
pp. 177-184
Author(s):  
Kewei Chen ◽  
◽  
Yasufumi Takama ◽  
Kaoru Hirota
Keyword(s):  
Fuzzy Inference ◽  
Molecular Layer ◽  
Atomic Layer ◽  
Complex Situation ◽  
Individual Layer ◽  
Tokyo Metropolitan Area ◽  
Multiple Depots ◽  
Decision Area ◽  
The Individual ◽  
Inference Methods

A new concept of the VDP/CD/MD problem (Vehicles Dispatching Problem for Cooperative Deliveries from Multiple Depots) and its formularization are proposed to provide a solver for the complex situation in the real new style transportation problem. An enhanced computational model with hierarchical multiplex structure, called the HIMS++ model, is introduced for the VDP/CD/MD problem. It contains 3 layers: the Atomic layer is a fluctuation area of system cost, the Molecular layer is a forming area of system state, and the Individual layer is a decision area of dispatching plan. The HIMS++ model is constructed as a software component using object-oriented paradigm. Its optimization algorithm is implemented through meta-heuristic and fuzzy inference methods. Experiments using 3-day order data taken from an actual dispatching center in Tokyo metropolitan area with 27 tank lorries (2 types) are done. It is confirmed that the HIMS++ model is very accurate (10%up) and fast (12 times) than the results given by the experts. The HIMS++ model is also a convenient tool (with few parameters and covering many objectives) for practical transportation problems.

scholarly journals A Mamdani Type Fuzzy Inference System to Calculate Employee Susceptibility to Phishing Attacks

2021 ◽  
Vol 11 (19) ◽  
pp. 9083
Author(s):  
Yahya Lambat ◽  
Nick Ayres ◽  
Leandros Maglaras ◽  
Mohamed Amine Ferrag
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Inference System ◽  
Human Error ◽  
Fuzzy Inference ◽  
Social Engineering ◽  
Rule Base ◽  
Inference System ◽  
Phishing Attacks ◽  
Future System ◽  
The Individual

It is a well known fact that the weakest link in a cyber secure system is the people who configure, manage or use it. Security breaches are persistently being attributed to human error. Social engineered based attacks are becoming more sophisticated to such an extent where they are becoming increasingly more difficult to detect. Companies implement strong security policies as well as provide specific training for employees to minimise phishing attacks, however these practices rely on the individual adhering to them. This paper explores fuzzy logic and in particular a Mamdani type fuzzy inference system to determine an employees susceptibility to phishing attacks. To negate and identify the susceptibility levels of employees to social engineering attacks a Fuzzy Inference System FIS was created through the use of fuzzy logic. The utilisation of fuzzy logic is a novel way in determining susceptibility due to its ability to resemble human reasoning in order to solve complex inputs, or its Interpretability and simplicity to be able to compute with words. This proposed fuzzy inference system is based on a number of criteria which focuses on attributes relating to the individual employee as well as a companies practices and procedures and through this an extensive rule base was designed. The proposed scoring mechanism is a first attempt towards a holistic solution. To accurately predict an employees susceptibility to phishing attacks will in any future system require a more robust and relatable set of human characteristics in relation to the employee and the employer.

scholarly journals Floating Car Data and Fuzzy Logic for classifying congestion indexes in the city of Shanghai

2019 ◽  
Vol 2 ◽  
pp. 1-7
Author(s):  
Maja Kalinic ◽  
Jukka M. Krisp
Keyword(s):  
Fuzzy Logic ◽  
Traffic Congestion ◽  
Fuzzy Inference ◽  
Inference Model ◽  
Floating Car Data ◽  
The Individual ◽  
The City

<p><strong>Abstract.</strong> In this paper, we use Floating Car Data from the city of Shanghai and Fuzzy Inference model to detect congestion indexes throughout the city. We aim to investigate to which extent traffic congestion is severe during afternoon rush hour. Additionally, we compare our results to the ones obtained by calculating congestion indexes on conventional way. Although we do not argue that our model is the best measure of congestion, it does allow the mechanism to combine different measures and to incorporate the uncertainty in the individual measures so that the compound picture of congestion can be reproduced.</p>

Developing a Measure of Traffic Congestion: Fuzzy Inference Approach

2002 ◽  
Vol 1802 (1) ◽  
pp. 77-85 ◽  
Author(s):  
Khaled Hamad ◽  
Shinya Kikuchi
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Fuzzy Inference ◽  
Supply And Demand ◽  
Travel Speed ◽  
Flow Speed ◽  
Inference Process ◽  
Real World Data ◽  
Total Travel Time ◽  
The Individual

Many measures have been proposed to represent the status of traffic conditions on arterial roadways in urban areas. The debate about what is the most appropriate measure continues. In a contribution to the debate, another approach was offered. Traditionally, two general approaches exist. One is based on the relationship between supply and demand. The other is a measure relative to the most acceptable status of service quality. The latter measure allows the public to relate to their travel experience. In either case, however, derivation of measures of congestion involves uncertainty because of imprecision of the measurement, the traveler’s perception of acceptability, variation in sample data, and the analyst’s uncertainty about causal relations. A measure is proposed that is a composite of two traditional measures, travel speed and delay. In recognition of the uncertainty, a fuzzy inference process was proposed. The inputs are travel speed, free-flow speed, and the proportion of very low speed in the total travel time. These values were processed through fuzzyrule-based inference. The outcome was a single congestion index value between 0 and 1, where 0 is the best condition and 1 is the worst condition. The process was demonstrated using real-world data. The results were compared with those of the Highway Capacity Manual. Although no conclusion can be drawn about the best measure of congestion, the proposed inference process allows the mechanism to combine different measures and also to incorporate the uncertainty in the individual measures so that the composite picture of congestion can be reproduced.

Formation of a Science-Based Real Estate Services Market Management Mechanism

2018 ◽  
Vol 931 ◽  
pp. 1172-1177
Author(s):  
Ekaterina V. Voronina ◽  
Viktor E. Reutov ◽  
Olga B. Yarosh ◽  
Sergei V. Khalezin
Keyword(s):  
Real Estate ◽  
Fuzzy Inference ◽  
Real Estate Market ◽  
Membership Functions ◽  
The Real ◽  
The Real Estate ◽  
Object State ◽  
Market Management ◽  
The Individual ◽  
Inference Systems

The authors approve a mathematical model for estimating the value of an object taking into account trends in the residential real estate market in the MATLAB software package with the assignment and correction of the fuzzy set membership functions. Fuzzy computations are performed using the Mamdani method, which requires defining the membership functions for the output variables. We consider schemes for constructing systems of fuzzy inference for variables (the real estate object state) and (the real estate market state). The results of calculations using the Fuzzy Logic Toolbox are given on the surfaces of fuzzy inference systems that show the dependence of the output variables on the individual input variables.

scholarly journals Dynamic Modeling of a Reformed Methanol Fuel Cell System Using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

2013 ◽  
Vol 11 (2) ◽  
Author(s):  
Kristian K. Justesen ◽  
Søren Juhl Andreasen ◽  
Hamid Reza Shaker
Keyword(s):  
Fuel Cell ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Cell Model ◽  
Empirical Methods ◽  
Inference System ◽  
System Models ◽  
Neuro Fuzzy ◽  
The Individual ◽  
Methanol Fuel Cell

In this work, a dynamic matlab Simulink model of an H3-350 reformed methanol fuel cell (RMFC) stand-alone battery charger produced by Serenergy® is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous hydrogen, which is difficult and energy-consuming to store and transport. The models include thermal equilibrium models of the individual components of the system. Models of the heating and cooling of the gas flows between components are also modeled and adaptive neuro-fuzzy inference system models of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other's output. The models take this into account using an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model, which is adapted to fit the measured performance of the H3-350 module. All of the individual parts of the model are verified and fine-tuned through a series of experiments and are found to have mean absolute errors between 0.4% and 6.4% but typically below 3%. After a comparison between the performance of the combined model and the experimental setup, the model is deemed to be valid for control design and optimization purposes.

scholarly journals Dynamic Modeling of a Reformed Methanol Fuel Cell System Using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

2013 ◽  
Author(s):  
Kristian K. Justesen ◽  
Søren J. Andreasen ◽  
Hamid R. Shaker
Keyword(s):  
Fuel Cell ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Cell Model ◽  
Empirical Methods ◽  
Inference System ◽  
System Models ◽  
Neuro Fuzzy ◽  
The Individual ◽  
Methanol Fuel Cell

In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy® is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous hydrogen, which is difficult and energy consuming to store and transport. The models include thermal equilibrium models of the individual components of the system. Models of the heating and cooling of the gas flows between components are also modeled and Adaptive Neuro-Fuzzy Inference System models of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified and fine-tuned through a series of experiments and are found to have mean absolute errors between 0.4% and 6.4% but typically below 3%. After a comparison between the performance of the combined model and the experimental setup, the model is deemed to be valid for control design and optimization purposes.

scholarly journals Estimation of fines amount in syariah criminal offences using adaptive neuro-fuzzy inference system (ANFIS) enhanced with analytic hierarchy process (AHP)

2019 ◽  
Vol 9 (6) ◽  
pp. 5537
Author(s):  
Ahmad Fitri Mazlam ◽  
Wan Nural Jawahir Hj Wan Yussof ◽  
Rabiei Mamat
Keyword(s):  
Analytic Hierarchy Process ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Individual Decision ◽  
Criminal Cases ◽  
Analytic Hierarchy ◽  
Inference System ◽  
Neuro Fuzzy ◽  
The Individual ◽  
Hierarchy Process

<span lang="EN-US">All syariah criminal cases, especially in khalwat offence have their case-fact, and the judges typically look forward to all the facts which were tabulated by the prosecutors. A variety of criteria is considered by the judge to determine the fines amount that should be imposed on an accused who pleads guilty. In Terengganu, there were ten (10) judges, and the judgments were made by the individual decision upon the trial to decide the case. Each judge has a stake, principles and distinctive criteria in determining fines amount on an accused who pleads guilty and convicted. This research paper presents an Adaptive Neuro-fuzzy Inference System (ANFIS) technique combining with Analytic Hierarchy Process (AHP) for estimating fines amount in Syariah (khalwat) criminal. Datasets were collected under the supervision of registrar and syarie judge in the Department of Syariah Judiciary State Of Terengganu, Malaysia. The results showed that ANFIS+AHP could estimate fines efficiently than the traditional method with a very minimal error.</span>

scholarly journals Presenting an Optimization Model for Performing Health Care Tasks by the Iranian Government

2020 ◽  
Vol 24 (5) ◽  
pp. 454-461
Author(s):  
Mohammad Reza Salary ◽  
◽  
Farajollah Rahnavard ◽  
Naser Hamidi ◽  
Gholamreza Memarzadeh Tehran ◽  
...  
Keyword(s):  
Health Care ◽  
Civil Society ◽  
Optimization Model ◽  
Fuzzy Inference ◽  
Optimal Performance ◽  
Inference System ◽  
Individual Level ◽  
Iranian Government ◽  
The Government ◽  
The Individual

Background: Optimal performance of health care tasks by the government in a way that promotes public health and development of the country is one of the most important pillars of governance. Objective: This study aims to present an optimization model for performing health care tasks by the Iranian government. In this model, the optimal interaction of governmental actors at the three action levels of governance (individual, organizational, and systemic) is examined. Methods: This is an applied descriptive study. Participants were 8 governmental management experts and 350 managers and deputies of the public, private, and non-governmental organizations in Iran. Data were collected by a researcher-made questionnaire. For designing the research model, fuzzy inference system was used. Findings: Promoting health care at the individual, organizational, and systemic levels was effective in optimally performance of the health care tasks by the government. At the individual level, civil society had a more important role, while the private and public sectors had a more important at the organizational and systemic levels, respectively. Conclusion: For optimal performance of macro-tasks in the field of health care, the Iranian government needs to pay more attention to the interaction of civil society and the private, public, and military sectors.

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