Making of fuzzy logic system rules base for decision making support by aggregation of weights of rules premises

Božanić, Darko; Pamučar, Dragan

doi:10.5937/tehnika1401129b

Cited by 7 publications

(9 citation statements)

References 8 publications

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“…Bazsova [21] selects members of the project management team using the AHP method. Božanić and Pamučar [22] select a military unit to remove explosive barriers using a fuzzy logic system. To form an elite security team, Dadelo et al [23] use the TOPSIS and SAW methods.…”

Section: Introductionmentioning

confidence: 99%

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

et al. 2021

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The paper presents a hybrid model for decision-making support based on D numbers, the FUCOM method and fuzzified RAFSI method, used for solving the selection of the group of construction machines for enabling mobility. By applying D numbers, the input parameters for the calculation of the weight coefficients of the criteria were provided. The calculation of the weight coefficients of the criteria was performed using the FUCOM method. The best alternative was selected using the fuzzified method, which was conditioned by the specificity of the issue so that in this case, the selection of the best alternative was made using the fuzzified RAFSI method.

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Section: Introductionmentioning

confidence: 99%

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

et al. 2021

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“…All rules for the fuzzy logic system are determined by applying the aggregation weight premise rules method (ATPP), Božanić and Pamučar (2014). There are many methods for constructing a rule base of a fuzzy logic system from a known set of numerical values, but the ATPP method allows the creation of a rule base based on experience and intuition.…”

Section: Forming a Database Of Rulesmentioning

confidence: 99%

“…The distribution of the weight coefficients of the membership functions should reflect reality as much as possible. In this particular case, w (xi) (j) was determined by interviewing experts and applying the FUCOM (Full Consistency Method) method (Pamučar et al, 2018), (Bozanic et al, 2019), (Fazlollahtabar et al, 2019), (Puška et al, 2019), (Erceg & Mularifović, 2019), (Durmić, 2019), (Nenadić, 2019), (Žižović & Pamucar, 2019), (Bozanic et al, 2020), (Durmić et al, 2020). Three experts were interviewed, and the results of the calculation of the weight coefficients are shown in Table 5.…”

Section: Most Often W (Xi)mentioning

confidence: 99%

Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

Milošević¹,

Pamučar²,

Chatterjee³

2021

Vojnotehnički glasnik

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Introduction/purpose: The paper presents a model for the selection of a route for the transport of hazardous materials using fuzzy logic systems, as a type of artificial intelligence systems. The system presented in the paper is a system for assistance in the decisionmaking process of the traffic service authorities when choosing one of several possible routes on a particular path when transporting hazardous materials. Methods: The route evaluation is performed on the basis of five criteria. Each input variable is represented by three membership functions, and the output variable is defined by five membership functions. All rules in a fuzzy logic system are determined by applying the method of weight premise aggregation (ATPP), which allows the formation of a database based on experience and intuition. Based on the number of input variables and the number of their membership functions, the basic base of 243 rules is defined. Three experts from the Ministry of Defense were interviewed to determine the weighting coefficients of the membership functions, and the values of the coefficients were determined using the Full Consistency Method (FUCOM). Results: A user program which enables the practical application of this model has been created for the developed fuzzy logic system. Conclusion: The user platform was developed in the Matlab 2008b software package.

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“…The characteristics of such a rule base depend on the number and quality of the experts, as well as the ability of the analysts to formulate their decisionmaking strategy. Due to the specificity of the model for selecting construction materials a new process was used for developing the FLS base: the method of aggregating the weights of rule premises (AWRP) [33].…”

Section: Forming the Base Of Rulesmentioning

confidence: 99%

Multi-Criteria Model for the Selection of Construction Materials: An Approach Based on Fuzzy Logic

Obradović

Pamučar

2020

Teh. vjesn.

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The process of construction and exploitation of a building passes through the preparation phase, the construction phase and the exploitation phase. Each of these phases involves the selection of criteria and decision making, with the aim of selecting the optimal construction materials for the building. The paper presents a new model for selecting construction materials that is based on fuzzy logic. In order to simulate the expert process of assessing the construction and exploitation of a building during which construction materials are selected, a modular fuzzy logic system was designed with a unique base of knowledge to assist in decision making on the priorities of the construction material. The model consists of four modules that are hierarchically organized on two levels. The size of the output from the model is the measure of a material's priority. Each of the materials observed (straw, wood, brick and concrete-steel) is assigned a certain value for the criterion function, on the basis of which the user of the system chooses the material for construction. In addition to the structure of the model, the paper presents its testing. Testing was carried out on the case study of selecting materials for the construction of five residential buildings.

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Making of fuzzy logic system rules base for decision making support by aggregation of weights of rules premises

Cited by 7 publications

References 8 publications

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

D Numbers – Fucom – Fuzzy Rafsi Model for Selecting the Group of Construction Machines for Enabling Mobility

Model for selecting a route for the transport of hazardous materials using a fuzzy logic system

Multi-Criteria Model for the Selection of Construction Materials: An Approach Based on Fuzzy Logic

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