Sugeno Methods Research Articles

COMPARISON OF SUGENO AND MAMDANI FUZZY SYSTEM PERFORMANCE IN PREDICTING THE AMOUNT OF VIRGIN COCONUT OIL (VCO) PRODUCTION

In the future, a tight industrial competition.The professional manage companies become crucial to successful so competitive on the global market.One of the key figure in production is the ability to plan and optimize goods production process. To face fluctuations of consumer demand without adding existing facilities, The company can use fuzzy mammal and sugeno methods to determine the amount of production of voc (virgin organic coconut) based on supply and demand data in the wotay coconut (main business area). process involving 18 fuzzy rules using AND and OR operators on each fuzzy set and IF-THEN rules for each input variable demand (little, medium, a lot), inventory (little, medium, a lot), output (little, medium , Lots). The thing that strengthens the conclusion that fuzzy sugeno is better than fuzzy mamdani with this data is that the MAPE for fuzzy sugeno has a value of 36.11% with a truth level of 63.89%, while for fuzzy mamdani the MAPE value is 38.77%, with a truth level 61.23 %. With the MAPE value obtained from Fuzzy Mamdani and Sugeno, the forecast for VOC production at KBU is predicted. Wootay Coconut is worth using with fuzzy sugeno.

Decision Support System to Determine The Price of Used Computer Based On Specification and Usage Duration Using Fuzzy Logic

Using computers at work or others has many positive impacts, including a special program that simplifies data and media processing. Certain software applications will, for some time, require high computer specifications. Many people have computers and want to fulfill the application requirements by selling computers to upgrade the specifications. However, some people are not very knowledgeable about calculating the cost of a used computer. One of the things that are done to make it easier for users to determine the price of a used computer is to create a decision support system that will assist in determining the price of a used computer based on specifications and usage duration. The Fuzzy Logic method was used in this study by comparing the accuracy results of the Fuzzy Mamdani and Sugeno methods. The parameters are based on the purchase price of all computer components, including Processor, Motherboard, RAM, SSD, HDD, VGA, PSU, and Case and usage duration. Fuzzy Mamdani is proven to have a higher accuracy with a value of 71% when compared to Fuzzy Sugeno. Based on measurement findings and a comparison of the methods used. Therefore, Fuzzy Mamdani is recommended for future studies using the same parameters. The benefits of this research include a recommendation system that will make it simpler for the general public to determine the selling price of used computers based on their specifications and usage duration. Another advantage is that it makes it easier for the general population to become a reference when buying or selling used computers, mainly assembled computers.

Egg Incubator Temperature and Humidity Control Using Fuzzy Logic Controller

Controlling room temperature and humidity in egg incubator systems is a process that is widely used in the farm. A good temperature and humidity for standard egg hatching is between 35℃ – 40℃, with humidity in the machine ranging from 50%-60%. The main problems of our research is to find the robustness of the fuzzy logic controller, using the proper parameter. Because while the particular parameter is applicable for one case, but after using several times, the controller lost its robustness. Therefore, this study aims to create a system to control the temperature and humidity of the egg incubator with fuzzy control using the Sugeno methods. In order to get the input and output values, namely by connecting the DHT22 sensor to measure temperature and humidity to be processed into the microcontroller, the value obtained from the sensor will then be processed. The use of fuzzy control is used to make several stages, namely fuzzification, rule, and defuzzification which after processing will be used as output weights for the actuators used. In order to get the robust parameter, test was carried out 5 times with a test time of 18 minutes to get a stable value from the tool. By applying this, it can be concluded whether the system is reliable during different situation. The result shows that the average time for the system to get a stable humidity is 302 second. On the other hand, the average time for the system to get stable temperature is 342 second. The Mean Squared error for temperature is 1,715, while the Mean Squared Error for Humidity is 5,294. It can be concluded that the system controlled by fuzzy controller is robust, has a fast response and reliable.

Identification of Floods in Palembang Area Using Fuzzy Logic Method of Mamdani and Sugeno

Floods are one of the natural events that often occur, especially in areas that have a large population. Palembang is one of the cities in Sumatra Province which often experiences flooding due to its dense population and lack of infiltration areas. One way to improve flood preparedness is to identify floods by using fuzzy logic. This study aims to identify floods in the Palembang area using fuzzy logic mamdani and Sugeno methods. Flood identification is carried out in 6 stages, namely variable determination, fuzzification, inference, application of fuzzy rules, defuzzification, and evaluation. The variables used in this study are rainfall, temperature, area elevation, and the results of flood identification that have a value of flood or not flood. The results of flood identification using the Mamdani method achieved an accuracy of 82% while the Sugeno method achieved an accuracy of 91%. The results of this study indicate that the mamdani and Sugeno fuzzy logic methods are quite good in identifying floods so that they can improve flood preparedness attitudes.

Diagnosa Penyakit Bells Palsy Menerapkan Metode Tsukamoto

Bell’s Palsy is paralysis of the facial muscles that causes one side of the face which causes one side of the face to sag. In Indonesia, there are many cases of bell's palsy but it is definitely difficult to determine. In this case, there was a case of bell's palsy in Indonesia of 19.55%, from all the most frequent cases of neuropathy that were found in the age of 20-50 years, and the incidence increased with increasing age after 60 years. About 60-85% of sufferers can recover completely within 3 weeks and only 15% require 3 months. But there are 30% of those who have a lifetime disability due to the patient not getting better for 4 months. Therefore an expert system was designed to diagnose bells palsy. The method used in the expert system is the Tsukamoto Method. The Tsukamoto method is a development of the Mamdani and Sugeno methods which use control and are also used by humans instead of machines. Fuzzy Tsukamoto is one method that is very flexible and has a tolerance for existing data. This expert system can provide solutions and ways to prevent bell's palsy with the diagnosis process carried out efficiently and save time in helping the general public in the prevention that occurs. This web-based expert system application was built with the PHP programming language and MySQL data storage

Study of a Weather Prediction System Based on Fuzzy Logic Using Mamdani and Sugeno Methods

Weather is a very important factor in supporting various human activities. However, weather is a natural event that keeps on changing due to various air conditions that affect it. One way to anticipate weather changes that may occur early is to create a system that can predict weather changes. Fuzzy logic is one of the methods that can be used in system prediction to find out the cause at a certain time and place. In this system, two fuzzy logic methods were used, they are the Mamdani and Sugeno methods, with three supporting criteria, including air temperature, humidity, and air pressure. In this research, data levers were carried out in June 2022 and resulted in a percentage accuracy of 73.34% for the Mamdani method and 70% for the Sugeno method.

Comparative Analysis using Tsukamoto and Sugeno Methods of Fuzzy Inference System for Sales of Medicine

This case study has been implemented on the apothecary shop located at Kotabumi city at Lampung province, Indonesia that selling various types of medicine. An apothecary in his scientific efforts need by prediction to a hypothetical for determining the amount of in the demand and the purchase of the new term, which has a challenge on increasing the purchasing amount and reflected the bank sound assets. A prediction used was to analyzed from the results of the comparison a method of Tsukamoto and Sugeno by using the nine rules and comparison to the value of absolute error of the purchase. Based on a the Sugeno method, the absolute error of the purchase was 0.0176 %, which is the lowest value in the study

Partial Discharge Localization in Oil through Acoustic Emission Technique Utilizing Fuzzy Logic

This study presents an examination of partial discharge (PD) localization in oil based on acoustic emission technique utilizing fuzzy logic. First, the PD measurement and localization systems are developed. In total, 2 coordinates of needle-plane electrodes that represent the PD location and 336 acoustic emission sensor (AES) coordinates are examined. The electrical PD is measured through an impedance matching circuit (IMC). The acoustic PD is acquired through AES and its signal is boosted by a preamplifier gain unit. The acoustic and electrical PDs are collected once the voltage reaches 30 kV. The data are first preprocessed by discrete wavelet transform (DWT) whereby it will be further analyzed by time of arrival (TOA), fuzzy logic Mamdani (FLM), and fuzzy logic Takagi–Sugeno (FLTS) methods. The arrival of time and distance between PD and AES are calculated based on TOA to find the PD location. Next, TOA and distance to PD location are used to define the input and output membership functions for FLM and FLTS to determine the PD location. It is found that FLTS has a great potential to be used for localization of the PD in oil whereby it has the lowest errors between actual PD location and AES. The performance of FLM and TOA is inferior to FLTS whereby the errors between actual PD location and AES are quite high for both PD locations.

Time Control Nebulizer Operation Using Fuzzy Sugeno Method

Nebulizer is one of the electro medic devices that serve to provide therapy for patients who experience abnormalities or disorders of the respiratory tract. Nebulizer system works using piezo electronic device to produces high frequency vibration. With this high frequency vibration the drug liquid molecules breaks down become fumes, thus it can easily to inhale for patient even for children. Unfortunately like other aerosol drug delivery system, the operation of nebulizer is also still manual. The patient doesn’t really know when the drug is empty on the canister. The nurses also need to check in regularly to see if the drugs are empty or not. In this paper a fuzzy sugeno methods is used to give prediction of nebulizer time operational. We propose fuzzy sugeno to calculate the time operational nebulizer using two parameters, such as drug droplet size and drug liquid volumes that have been administer by nurses. Using fuzzy sugeno method we can solve the nebulizer manual operational time problem. Our result show that the longest operational time was 26.07 minutes, this achieve when liquid volume was 5 ml and the size of drug droplet was 1 um. Meanwhile for the shortest operational time was 8.07 minutes, this achieve when liquid volume was 10 ml and the size of drug droplet was 4 um. We can conclude that we had successful to control nebulizer operational time using fuzzy sugeno method.

Study and Implementation of the Fuzzy Mamdani and Sugeno Methods in Decision Making on Selection of Outstanding Students at the South Aceh Polytechnic

The selection of students who excel academically is a measure of the quality of education in an educational institution. In the implementation of education, student achievement becomes a measure of the success of education at the institution. Achievement is the result of hard work by following the rules given by a certain person or institution with certain criteria and conditions to determine if someone is eligible to be chosen as an award recipient. This research uses the Mamdani Fuzzy method or Fuzzy inference system and Sugeno Fuzzy, to design this decision-making system is to design the decision results from the rules compiled using Matlab software for testing. The South Aceh Polytechnic holds outstanding student elections every year, the selection of students with achievements that are carried out every year only focuses on the GPA value in academic achievement without looking at the determining factors which are more precise. In the research that will be conducted the selection must meet the eligibility criteria as a student who gets an award or as an outstanding student at the South Aceh Polytechnic involving variables in the form of Cumulative Achievement Index, Final Project value, Extracurricular, and Attendance. Research is expected to be a tool in the selection process for candidate participants who compete in the selection of outstanding students at the South Aceh Polytechnic so that relevant departments in universities can determine the eligibility of prospective students as award recipients as students with the best achievement scores by considering the appropriate determining factors. The expected output using the Mamdani and Sugeno fuzzy method can become an intellectual property system so that this system can be selected as a guideline by the South Aceh Polytechnic academic for determining outstanding students. The results of the research that have been obtained show that the level of truth is 86.82% for the Mamdani method while the implementation of Sugeno Fuzzy logic is obtained a level of truth of 71.88%

Differentiation of Mamdani and Sugeno Fuzzy Inference System in developing Automatic Plant Watering Systems for Domestic Use

Water management systems are an essential requirement for maintaining plants. One of the major problems encountered in growing plants in houses, offices or buildings with in-house kitchen gardens is irregular irrigation patterns. This leads to over irrigation of pots or elongated durations of dry soil, both conditions ill for plant growth. This problem is further aggravated when manual irrigation ignores the environmental conditions and plant specific requirements. Utilizing Fuzzy logic for developing Automatic Plant watering systems provide flexibility in manipulating input parameters such as Temperature, Humidity, Soil Moisture and Plant Growth to determine optimum flow rate of the irrigation system. In this study, multiple fuzzy systems are developed for different environments and parameters. MATLAB is used for designing the fuzzy logic controllers using both Mamdani and Sugeno Models. The requirement for the system is to adjust the flow rate in accordance with the environmental conditions and plant requirements. The paper draws comparison between Mamdani and Sugeno methods on the basis of their performance characteristics for different environments. It also provides development of an effective controller for a watering system for household plantations.

ANALISA PERBANDINGAN FUZZY LOGIC METODE TSUKAMOTO, SUGENO, MAMDANI DALAM PENENTUAN KELUARGA MISKIN

The application of the Fuzzy Tsukamoto, Sugeno, and Mamdani methods in determining poor families in Sumedang Regency can be done by the three methods using poor family outcomes which differ from the results of all data calculations. From all data calculated using the fuzzy logic method of the Tsukamoto, Sugeno, and Mamdani methods, it can be concluded that there are 4 data classified as poor and 16 data classified as not poor in the Tsukamoto method, 8 data classified as poor and 12 data classified not poor in the Sugeno method, and 10 data classified as poor and 10 classified as not poor in the Mamdani method. These results indicate that each method has different results even though the input used is the same.

Penentuan Server Kritis Dengan Menggunakan Fuzzy Mamdani Dan Fuzzy Sugeno Pada PT SAMUDERA INDONESIA TBK

PT Samudera Indonesia Tbk merupakan perusahaan yang bergerak dalam bidang jasa yang berupa logistik. Sebagai perusahaan jasa, sangat mengutamakan pelayanan terutama dalam memberikan layanan informasi kepada customer atau client. Namun, dalam sering terjadi masalah teknologi sistem informasi yang digunakan khususnya yang terjadi adalah server down. Hal ini disebabkan beberapa faktor tidak bisa diprediksi. Ditambah lagi perusahaan ini masih bergantung kepada peranan personil IT untuk menunggu penanganan kejadian server down. Upaya mengetahui tingkat kritis server adalah salah satu pencegahan atau mitigasi terhadap gangguan yang beresiko fatal terhadap proses bisnis perusahaan maka dibutuhkan sistem pendukung keputusan. Dalam penelitian ini, penulis membandingkan perhitungan metode logika fuzzy mamdani dengan metode fuzzy sugeno untuk mengukur tingkat kritis server yang digunakan PT Samudera Indonesia Tbk. Penelitian ini menghasilkan sebuah Prototipe yang dibangun dengan Matlab R2013a, dapat digunakan untuk menghitung tingkat kritis pada server. Prototipe tersebut menggunakan dua metode fuzzy mamdani dan fuzzy sugeno. Metode fuzzy mamdani memiliki akurasi rata-rata 85,21%. Dari perhitungan kedua metode tersebut, hasil nilai akurasi yang tertinggi akan dijadikan sebagai acuan dalammenentukan server yang kritis.Kata Kunci: SPK, Server, fuzzy mamdani, fuzzy sugeno, Matlab R2013a

INFORMATION SUPPORT FOR THE ANALYSIS OF SKILLS AND ABILITIES OF UNIVERSITY STUDENTS

In the below article, the application of the fuzzy logical conclusion method is considered as decision-maker in the process of analyzing the students skills and abilities based on the requirements of potential employers, in order to reduce the time of the first interview for potential candidates on a vacant position. When analyzing the results of the assessment of the competence of university students, a certain degree of fuzziness arises. In modern practice, fuzzy logic is used in many different assessment methods, including questioning, interviewing, testing, descriptive method, classification method, pairwise comparison, rating method, business games competence models, and the like. Each of the methods has its advantages and disadvantages, but they are effective only as part of a unified personnel management system. As a method for implementing a systematic approach to the assessment of the contingent of students, it is proposed to use fuzzy logic, a mathematical apparatus that allows you to build a model of an object based on fuzzy judgments. The use of fuzzy logic, the mathematical apparatus of which allows you to build a model of the object, based on fuzzy reasoning and rules. The most important condition for creating such a model is to translate the fuzzy, qualitative assessments used by man into the language of mathematics, which will be understood by the computer. The most used are fuzzy inferences using the Mamdani and Sugeno methods. In a fuzzy inference of the Mamdani type, the value of the output variable is given by fuzzy terms, in the conclusion of the Sugeno type, as a linear combination of the input variables. Research in the field of application of fuzzy logic in socio-economic systems suggests that it can be used to assess the competencies of university students.

Ensemble of evolving data clouds and fuzzy models for weather time series prediction

This paper describes a variation of data cloud-based intelligent method known as typicality-and-eccentricity-based method for data analysis (TEDA). The objective is to develop data-centric nonlinear and time-varying models to predict mean monthly temperature. TEDA is an incremental algorithm that considers the data density and scattering of clouds over the data space. The method does not require a priori knowledge of the dataset and user-defined parameters. However, if some knowledge about the number of clouds and rules is available, then it can be expressed through a single parameter. Past values of minimum, maximum and mean monthly temperature, as well as previous values of exogenous variables such as cloudiness, rainfall and humidity are considered in the analysis. A non-parametric Spearman correlation based method is proposed to rank and select the most relevant features and time delays for a more accurate prediction. The datasets were obtained from weather stations located in main Brazilian cities such as Sao Paulo, Manaus, Porto Alegre, and Natal. These cities are known to have particular weather characteristics. TEDA results are compared with results provided by the evolving Takagi–Sugeno (eTS) and the extended Takagi–Sugeno (xTS) methods. Additionally, an ensemble of cloud and fuzzy models and fuzzy aggregation operators is developed to give single-valued and granular predictions of the time series. Granular predictions convey a range of possible temperature values and give an idea about the error and uncertainty associated with the data.

A novel approach to detect respiratory phases from pulmonary acoustic signals using normalised power spectral density and fuzzy inference system.

Monitoring respiration is important in several medical applications. One such application is respiratory rate monitoring in patients with sleep apnoea. The respiratory rate in patients with sleep apnoea disorder is irregular compared with the controls. Respiratory phase detection is required for a proper monitoring of respiration in patients with sleep apnoea. To develop a model to detect the respiratory phases present in the pulmonary acoustic signals and to evaluate the performance of the model in detecting the respiratory phases. Normalised averaged power spectral density for each frame and change in normalised averaged power spectral density between the adjacent frames were fuzzified and fuzzy rules were formulated. The fuzzy inference system (FIS) was developed with both Mamdani and Sugeno methods. To evaluate the performance of both Mamdani and Sugeno methods, correlation coefficient and root mean square error (RMSE) were calculated. In the correlation coefficient analysis in evaluating the fuzzy model using Mamdani and Sugeno method, the strength of the correlation was found to be r = 0.9892 and r = 0.9964, respectively. The RMSE for Mamdani and Sugeno methods are RMSE = 0.0853 and RMSE = 0.0817, respectively. The correlation coefficient and the RMSE of the proposed fuzzy models in detecting the respiratory phases reveals that Sugeno method performs better compared with the Mamdani method.

Type-2 fuzzy hybrid expert system for prediction of tardiness in scheduling of steel continuous casting process

This paper addresses an interval type-2 fuzzy (IT2F) hybrid expert system in order to predict the amount of tardiness where tardiness variables are represented by interval type-2 membership functions. For this purpose, IT2F disjunctive normal forms and fuzzy conjunctive normal forms are utilized in the inference engine. The main contribution of this paper is to present the IT2F hybrid expert system, which is the combination of the Mamdani and Sugeno methods. In order to predict the future amount of tardiness for continuous casting operation in a steel company in Canada, an autoregressive moving average model is used in the consequents of the rules. Parameters of the system are tuned by applying Adaptive-Network-Based Fuzzy Inference System. This method is compared with IT2F Takagi–Sugeno–Kang method in MATLAB, multiple-regression, and two other Type-1 fuzzy methods in literature. The results of computing the mean square error of these methods show that our proposed method has less error and high accuracy in comparison with other methods.

Use of fuzzy logic for modeling the growth of Fe2B boride layers during boronizing

In this study, the evaluation of the phase Fe2B growth in AISI 1045 steel during paste boronizing was carried out. Fuzzy logic Mamdani and Takagi–Sugeno methods were used as the technical model. The experimental procedure was performed in a solid paste medium, at temperatures range of 1193–1273 K; for 2, 4 and 6 h; and modifying the boron potential (paste thickness) at the metal surface. Membership functions were proposed for fuzzification and defuzzification of the input and output values. The system structure utilized was based on two membership functions for the input (time and paste thickness), and one for the output (layer growth). Comparing the results, given by the fuzzy logic system with experimental data, the medium error generated from the Mamdani method was 2.61%, and from the Takagi–Sugeno was 3.62%. It is concluded that the technique of fuzzy logic is an alternative for modeling the growth of borided phases.