A Decision Making Approach Using Fuzzy Logic and ANFIS: A Retail Study Case

Ulos batak toba is one of indonesia traditional fabric, precisely the traditional cloth of the batak toba. From time to time the ulos fabric was growing in terms of type and motif. One of the companies that produces ulos batak is cv. Ala dos roha. The authors conducted this study aimed at predicting the amount of production of ulos batak to produced later. The author uses the previous request, inventory and production data using fuzzy logic tsukamoto. The final result of the calculation with this method will be more effective and efficient so as to speed up the decision making time to predict the amount of production to be produced next.Keywords: prediction, amount of production, method of tsukamoto

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Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

Jurnal ULTIMA Computing ◽

10.31937/sk.v7i1.448 ◽

2016 ◽

Vol 7 (1) ◽

pp. 12-18

Author(s):

Joko Haryanto ◽

Seng Hansun

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Decision Support ◽

Decision Support System ◽

Support System ◽

System Application ◽

Prospective Students ◽

Fuzzy Logic Method ◽

Index Terms ◽

Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

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Faculty Opinions recommendation of Fuzzy sets and fuzzy logic in multi-criteria decision making. The 50th anniversary of Prof. Lotfi Zadeh's theory: introduction.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726229734.793516038 ◽

2016 ◽

Author(s):

Shripad Tuljapurkar

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Fuzzy Sets ◽

50Th Anniversary ◽

Multi Criteria Decision Making

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Application of Interval Fuzzy Logic in Selecting a Sustainable Supplier on the Example of Agricultural Production

Symmetry ◽

10.3390/sym13050774 ◽

2021 ◽

Vol 13 (5) ◽

pp. 774

Author(s):

Adis Puška ◽

Miroslav Nedeljković ◽

Sarfaraz Hashemkhani Zolfani ◽

Dragan Pamučar

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Asymmetric Information ◽

Agricultural Production ◽

Complete Information ◽

Sustainable Supply Chain ◽

Sustainability Criteria ◽

Criteria Importance ◽

Selection Of ◽

Economic Criteria

The selection of sustainable suppliers (SSS) is the first step in applying a sustainable supply chain and sustainable production. Therefore, it is necessary to select the supplier that best meets the set sustainability criteria. However, the selection of suppliers cannot be done by applying symmetric information, because the company does not have complete information, so asymmetric information should be used when selecting suppliers. Since the SSS applies three main sustainability criteria, environmental, social, and economic criteria, this decision-making problem is solved by applying multi-criteria decision-making (MCDM). In order to solve the SSS for the needs of agricultural production, interval fuzzy logic was applied in this research, and six suppliers with whom agricultural pharmacies in Semberija work were taken into consideration. The application of interval fuzzy logic was performed using the methods PIPRECIA (Pivot pairwise relative criteria importance assessment) and MABAC (Multi-Attributive Border Approximation Area Comparison). Using the PIPRECIA method, the weights of criteria and sub-criteria were determined. Results of this method showed that the most significant are economic criteria, followed by the social criteria. The ecological criteria are the least important. The supplier ranking was performed using the MABAC method. The results showed that supplier A4 best meets the sustainability criteria, while supplier A6 is the worst. These results were confirmed using other MCDM methods, followed by the sensitivity analysis. According to the attained results, agricultural producers from Semberija should buy the most products from suppliers A4, in order to better apply sustainability in production. This paper showed how to decision make when there is asymmetric information about suppliers.

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Fuzzy Logic for Intelligent Control System Using Soft Computing Applications

Sensors ◽

10.3390/s21082617 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2617

Author(s):

Catalin Dumitrescu ◽

Petrica Ciotirnae ◽

Constantin Vizitiu

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Soft Computing ◽

Intelligent Control ◽

Fuzzy Controller ◽

Control Technique ◽

Distributed Intelligence ◽

High Level ◽

The Impact ◽

Fuzzy Subsets

When considering the concept of distributed intelligent control, three types of components can be defined: (i) fuzzy sensors which provide a representation of measurements as fuzzy subsets, (ii) fuzzy actuators which can operate in the real world based on the fuzzy subsets they receive, and, (iii) the fuzzy components of the inference. As a result, these elements generate new fuzzy subsets from the fuzzy elements that were previously used. The purpose of this article is to define the elements of an interoperable technology Fuzzy Applied Cell Control-soft computing language for the development of fuzzy components with distributed intelligence implemented on the DSP target. The cells in the network are configured using the operations of symbolic fusion, symbolic inference and fuzzy–real symbolic transformation, which are based on the concepts of fuzzy meaning and fuzzy description. The two applications presented in the article, Agent-based modeling and fuzzy logic for simulating pedestrian crowds in panic decision-making situations and Fuzzy controller for mobile robot, are both timely. The increasing occurrence of panic moments during mass events prompted the investigation of the impact of panic on crowd dynamics and the simulation of pedestrian flows in panic situations. Based on the research presented in the article, we propose a Fuzzy controller-based system for determining pedestrian flows and calculating the shortest evacuation distance in panic situations. Fuzzy logic, one of the representation techniques in artificial intelligence, is a well-known method in soft computing that allows the treatment of strong constraints caused by the inaccuracy of the data obtained from the robot’s sensors. Based on this motivation, the second application proposed in the article creates an intelligent control technique based on Fuzzy Logic Control (FLC), a feature of intelligent control systems that can be used as an alternative to traditional control techniques for mobile robots. This method allows you to simulate the experience of a human expert. The benefits of using a network of fuzzy components are not limited to those provided distributed systems. Fuzzy cells are simple to configure while also providing high-level functions such as mergers and decision-making processes.

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A Kalman filtering fuzzy logic algorithm for recognition of lane departure

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189970 ◽

2021 ◽

pp. 1-8

Author(s):

Kai Ren

Keyword(s):

Decision Making ◽

Fuzzy Logic ◽

Kalman Filtering ◽

Traffic Accidents ◽

Region Of Interest ◽

Fuzzy Logic Algorithm ◽

The Road ◽

Departure Decision ◽

Lane Departure ◽

Fusion Analysis

In all kinds of traffic accidents, the unconscious departure of the vehicle from the lane is one of the most important reasons leading to the occurrence of these accidents. In view of the specific problem of lane departure, a lane departure decision-making method is established without calibration relying on the Kalman filtering fuzzy logic algorithm, according to the characteristics of expressway lanes, based on the machine vision and hearing fusion analysis of lane departure, integrating the extraction of the linear lane line model and the region of interest (ROI) in this paper to judge the degree of vehicle departure from the lane by integrating the slope values of the 2 lane lines in the road image. The results show that the system has good lane recognition capabilities and accurate departure decision-making capabilities, and meet the lane departure warning requirements in the expressway environment.

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Landscape Evaluation as a Complementary Tool in Environmental Assessment. Study Case in Urban Areas: Salamanca (Spain)

Sustainability ◽

10.3390/su12166395 ◽

2020 ◽

Vol 12 (16) ◽

pp. 6395

Author(s):

Marco Criado ◽

Antonio Martínez-Graña ◽

Fernando Santos-Francés ◽

Leticia Merchán

Keyword(s):

Decision Making ◽

Environmental Assessment ◽

Urban Areas ◽

Territorial Planning ◽

Assessment Study ◽

Management Measures ◽

Study Case ◽

Partial State ◽

Landscape Units ◽

Objective Methodology

In recent years, the landscape has become another environmental resource, so it is important to incorporate it into planning actions. However, its broad sense of study has made it difficult to develop methodologies that precisely diagnose the state of the landscape and its management requirements, especially in dynamic spaces like urban areas. In order to develop a method capable of providing information that can be incorporated into environmental assessment and territorial planning tasks so that the needs of the landscape are taken into account in the decision-making stages, an objective methodology is presented based on the study of different parameters (biotic, abiotic and socioeconomic) analyzed in the field and subsequently geoprocessed through Geographic Information Systems according to their influence on the landscape. Through the proposed methodology it is possible to determine the quality, fragility and need of protection of the landscape, as well as to identify the diverse landscape units that form the landscape of a territory. Based on these results, a landscape diagnosis can be drawn up to quantify its overall and partial state, carry out monitoring analyses and make comparisons between different landscape units, so that management measures can be adopted according to the obtained scenarios.

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