• Title/Summary/Keyword: CRISP

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FUZZY TRANSPORTATION PROBLEM WITH ADDITIONAL CONSTRAINT IN DIFFERENT ENVIRONMENTS

  • BUVANESHWARI, T.K.;ANURADHA, D.
    • Journal of applied mathematics & informatics
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    • v.40 no.5_6
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    • pp.933-947
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    • 2022
  • In this research, we presented the type 2 fuzzy transportation problem with additional constraints and solved by our proposed genetic algorithm model, and the results are verified using the softwares, genetic algorithm tool in Matlab and Lingo. The goal of our approach is to minimize the cost in solving a transportation problem with an additional constraint (TPAC) using the genetic algorithm (GA) based type 2 fuzzy parameter. We reduced the type 2 fuzzy set (T2FS) into a type 1 fuzzy set (T1FS) using a critical value-based reduction method (CVRM). Also, we use the centroid method (CM) to obtain the corresponding crisp value for this reduced fuzzy set. To achieve the best solution, GA is applied to TPAC in type 2 fuzzy parameters. A real-life situation is considered to illustrate the method.

A study of creative human judgment through the application of machine learning algorithms and feature selection algorithms

  • Kim, Yong Jun;Park, Jung Min
    • International journal of advanced smart convergence
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    • v.11 no.2
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    • pp.38-43
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    • 2022
  • In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

Implementation of a Sightseeing Multi-function Controller Using Neural Networks

  • Jae-Kyung, Lee;Jae-Hong, Yim
    • Journal of information and communication convergence engineering
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    • v.21 no.1
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    • pp.45-53
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    • 2023
  • This study constructs various scenarios required for landscape lighting; furthermore, a large-capacity general-purpose multifunctional controller is designed and implemented to validate the operation of the various scenarios. The multi-functional controller is a large-capacity general-purpose controller composed of a drive and control unit that controls the scenarios and colors of LED modules and an LED display unit. In addition, we conduct a computer simulation by designing a control system to represent the most appropriate color according to the input values of the temperature, illuminance, and humidity, using the neuro-control system. Consequently, when examining the result and output color according to neuro-control, unlike existing crisp logic, neuro-control does not require the storage of many data inputs because of the characteristics of artificial intelligence; the desired value can be controlled by learning with learning data.

A STUDY OF TWO SPECIES MODEL WITH HOLLING TYPE RESPONSE FUNCTION USING TRIANGULAR FUZZY NUMBERS

  • P. VINOTHINI;K. KAVITHA
    • Journal of applied mathematics & informatics
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    • v.41 no.4
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    • pp.723-739
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    • 2023
  • In this paper, we developed three theoretical models based on prey and predator that exhibit holling-type response functions. In both a fuzzy and a crisp environment, we have provided a mathematical formulation for the prey predator concept. We used the signed distance method to defuzzify the triangular fuzzy numbers using the alpha-cut function. We can identify equilibrium points for all three theoretical models using the defuzzification technique. Utilizing a variational matrix, stability is also performed with the two species model through three theoretical models. Results are presented, followed by discussion. MATLAB software is used to provide numerical simulations.

PROJECT SCHEDULING WITH START-TIME DEPENDENT COST AND IMPRECISE DURATION

  • Siamak Haji Yakhchali
    • International conference on construction engineering and project management
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    • 2011.02a
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    • pp.468-473
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    • 2011
  • The goal of a project manager is generally to minimize the cost of the project and also to cope with uncertainty. This paper deals with the problem of project scheduling a set of activities satisfying precedence constraints in order to minimize the sum of the costs associated with the starting times of the activities in the network with imprecise activity durations, represented by means of interval or fuzzy numbers. So far this problem has been completely solved by several authors when the activities durations have crisp values. However, they do not consider the imprecision in activity durations in their models. Here the framework of possibility theory is proposed to solve this problem. In fuzzy arithmetic, usually, the interval calculations are used for the aim of complexity reduction and simplification. Thus the case of interval-valued durations is first addressed, and then extended to fuzzy intervals. A numerical example is used to illustrate the developed concept.

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Application of AI-based Customer Segmentation in the Insurance Industry

  • Kyeongmin Yum;Byungjoon Yoo;Jaehwan Lee
    • Asia pacific journal of information systems
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    • v.32 no.3
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    • pp.496-513
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    • 2022
  • Artificial intelligence or big data technologies can benefit finance companies such as those in the insurance sector. With artificial intelligence, companies can develop better customer segmentation methods and eventually improve the quality of customer relationship management. However, the application of AI-based customer segmentation in the insurance industry seems to have been unsuccessful. Findings from our interviews with sales agents and customer service managers indicate that current customer segmentation in the Korean insurance company relies upon individual agents' heuristic decisions rather than a generalizable data-based method. We propose guidelines for AI-based customer segmentation for the insurance industry, based on the CRISP-DM standard data mining project framework. Our proposed guideline provides new insights for studies on AI-based technology implementation and has practical implications for companies that deploy algorithm-based customer relationship management systems.

OPTIMIZATION OF STOCK MANAGEMENT SYSTEM WITH DEFICIENCIES THROUGH FUZZY RATIONALE WITH SIGNED DISTANCE METHOD IN SEABORN PROGRAMING TOOL

  • K. KALAIARASI;N. SINDHUJA
    • Journal of applied mathematics & informatics
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    • v.42 no.2
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    • pp.379-390
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    • 2024
  • This study proposes a fuzzy inventory model for managing large-scale production, incorporating cost considerations. The model accounts for two types of expenditure scenarios-parametric and exponential. Uncertainty surrounds holding costs, setup costs, and demand rates. The approach considers a supply chain system with a complex manufacturing process, factoring in transportation costs based on the quantity of goods and distance between the supplier and retailer. The initial crisp model is then transformed into a fuzzy simulation, incorporating specific fuzzy variables affecting inventory costs. The proposed method significantly reduces overall inventory costs for the entire supply chain. Retailer demand is linked to inventory levels, and vendor/distributor storage deteriorates over time. The fuzzy condition assumes hexagonal variables for all associated factors. The study employs the signed distance method for defuzzification to determine the optimal order quantity with hexagonal fuzzy numbers. Mathematical examples are provided to illustrate the practicality of the proposed approach.

Centrifuge Model Test on the Bearing Capacity and Failure Mechanism of Composit Ground Improved with Slag Compaction Piles (슬래그 다짐말뚝으로 개량된 복합지반의 지지력 및 파괴메카니즘에 관한 원심모형실험)

  • Yoo Nam-Jae;Park Byung-Soo;Jeong Gil-Soo;Koh Kyung-Hwan;Kim Ji-Sung
    • Journal of the Korean Geotechnical Society
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    • v.21 no.1
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    • pp.59-67
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    • 2005
  • This paper presents experimental and numerical research results of centrifuge model tests performed to investigate the geotechnical engineering behavior of slag compaction pile as a substitute of sand compaction pile. For centrifuge model tests, bearing capacity of composit soil improved with slag compaction piles, stress concentrations in-between pile and soft clay, settlement characteristics, and failure modes were investigated with slags differing in their relative density. A slag was found to be a good substitute for a sand since the slag compaction pile model showed a greater yield stress intensity up to $30\%$ than the sand compaction pile model under the identical testing conditions. Stress concentration ratio tended to increase with the relative density of slag pile and the clear shear lines in the piles were observed at the depth of $2D{\sim}2.5D$ (D=dia. of model pile) from the top of the piles after loading tests. Numerical analysis with a software of CRISP, implemented with the modified Cam-clay model, was carried out to simulate the results of centrifuge model test. Test results about characteristics of load-settlement curves and stress concentration ratio are in relatively good agreements with numerical estimations.

The application of fuzzy spatial overlay method to the site selection using GSIS (GSIS를 이용한 입지선정에 있어 퍼지공간중첩기법의 적용에 관한 연구)

  • 임승현;조기성
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.17 no.2
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    • pp.177-187
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    • 1999
  • Up to date, in many application fields of GSIS, we usually have used vector-based spatial overlay or grid-based spatial algebra for extraction and analysis of spatial data. But, because these methods are based on traditional crisp set, concept which is used these methods. shows that many kinds of spatial data are partitioned with sharp boundary. That is not agree with spatial distribution pattern of data in the real world. Therefore, it has a error that a region or object is restricted within only one attribution (One-Entity-one-value). In this study, for improving previous methods that deal with spatial data based on crisp set, we are suggested to apply into spatial overlay process the concept of fuzzy set which is good for expressing the boundary vagueness or ambiguity of spatial data. two methods be given. First method is a fuzzy interval partition by fuzzy subsets in case of spatially continuous data, and second method is fuzzy boundary set applied on categorical data. with a case study to get a land suitability map for the development site selection of new town, we compared results between Boolean analysis method and fuzzy spatial overlay method. And as a result, we could find out that suitability map using fuzzy spatial overlay method provide more reasonable information about development site of new town, and is more adequate type in the aspect of presentation.

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Quality of Sweet Corn Stored at Different Temperatures and Duration (저장온도와 기간에 따른 단옥수수의 품질변화)

  • 이석순;이상직;김대연
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.32 no.2
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    • pp.137-143
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    • 1987
  • To find out the optimum storage temperature and duration, changes in the content of sugars and soluble solids and flavor rate of two sweet corn hybrids (Great Bell and Golden Cross Bantam) and a super sweet corn (Crisp Super Sweet 720) were observed after storing at -20, 0, 5, 10, 15, 20, and 25$^{\circ}C$ for 1,3,5, and 7 days. At the temperatures below 10$^{\circ}C$, contents of soluble solids and total sugars and flavor rate were not changed significantly, but at the temperatures higher than 15$^{\circ}C$ they decreased as storage temperatures increased and duration extended. Storage duration conserving flavor seems to be 7 days at temperatures below 10$^{\circ}C$, 3 days at 15$^{\circ}C$, and 1-2 days at 25$^{\circ}C$. When corn was frozen, flavor rate was a little low compared with corn stored at 0$^{\circ}C$ although sugar content was higher. Both soluble solids and total sugar contents were positively correlated with flavor rate of cooked corn.

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