Construction of Knowledge Base for Clothing Sensory Design

2011 ◽  
Vol 175-176 ◽  
pp. 811-816
Author(s):  
Hong Lu ◽  
Yan Chen ◽  
Hong Qin Dai
Keyword(s):  
Knowledge Base ◽  
Fuzzy Numbers ◽  
Semantic Space ◽  
Design Rule ◽  
Basic Rule ◽  
Card Sorting ◽  
Body Type ◽  
Analytic Hierarchy ◽  
Design Elements ◽  
Sensory Design

In this paper, the contents of knowledge base for clothing sensory design are defined as four parts: the clothing design elements, semantic expression, reflection between the former two and design rules. The character and contents of each part are discussed and analyzed respectively. Methods of interviewing, laddering, card sorting, analytic hierarchy process (AHP), Hierarchy structure, triangle fuzzy numbers, literature reviewing etc. are chosen for the knowledge elicitation and representation. The men’s suit is used as a case study to explain the whole procedure of knowledge base construction. The style design elements of the men’s suit are decomposed into 9 items and 28 categories. The semantic space of the sensory evaluation towards the men’s suit is modelled in the form of 4 word-pairs: formal- casual, classical- modern, gorgeous- simple and elegant- masculine. The triangular fuzzy numbers are introduced to quantify the 7-point scales of linguistic descriptions (extreme, very, rather, average, rather, very and extreme). And the reflection of the design elements space and semantic space is acquired and represented. The design rule of the men’s suit is obtained by the method of literature reviewing and interviewing. It includes both the basic rule derived from the beauty rule and the design principle based on consumers’ character such as body type and facial colour etc. All techniques and methods are not limited to men’s suit itself but can be extended to other garments or products. The conclusions of the paper will play an important role in realizing the goals such as clothing individuation, sensation, intellectualization and fashion etc.

scholarly journals Investigation on Agricultural Land Selection using Hybrid Fuzzy Logic System

2020 ◽  
Vol 21 (4) ◽  
pp. 569-582
Author(s):  
Sudhakar Sengan ◽  
Vijayakumar V ◽  
Sujatha Krishnamoorthy ◽  
Gunasekaran S ◽  
Sathiya Kumar C ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Numbers ◽  
Agricultural Land ◽  
Test Results ◽  
Analytic Hierarchy ◽  
Fuzzy Degree ◽  
Hierarchy Process ◽  
Inherent Ambiguity ◽  
Different Levels ◽  
Logic System

For maintaining the horticultural generation, Land Selection Investigation (LSI) is essential. Though incorporates estimation of the criteria assortment from the soil, territory to financial, market, and foundation, and these components are considerably enigmatically characterized and described by their inherent ambiguity. Multi-criteria basic leadership systems like positioning, rating, and so on are utilized for reasonableness examination. Master learning and judgment by leaders at different levels is integrated into this process. In the field of farming sciences, the Fuzzy Logic (FL) strategy has been effectively used to take care of numerous issues. Fuzzy with AHP is a Hybrid Fuzzy Logic (HFL) methodology. The policies Analytic Hierarchy Process(AHP), Fuzzy Numbers, Fuzzy Degree Investigation, Alpha Cut, and Lambda capacity are associated with it. As expressed, the procedure of necessary leadership includes a scope of criteria and a considerable measure of master learning and decisions. The components result from impacts extraordinarily. The capacity of three methods to demonstrate the affectability of the necessary leadership procedure is researched. Alpha cut and lambda esteem give and encourage considerable affectability investigation. All techniques are actualized to examine the reasonableness of the crop in the Indian nation. Test results when performed on various datasets, demonstrate that the proposed procedure removes more highlights just as gives more exactness when  contrasted with existing techniques.

Application of Shannon’s entropy-analytic hierarchy process (AHP) for the selection of the most suitable starch as matrix in green biocomposites for takeout food packaging design

BioResources ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 4065-4088
Author(s):  
H. N. Salwa ◽  
S. M. Sapuan ◽  
M. T. Mastura ◽  
M. Y. M. Zuhri
Keyword(s):  
Analytic Hierarchy Process ◽  
Food Packaging ◽  
Shannon’S Entropy ◽  
Rice Starch ◽  
Sago Starch ◽  
Analytic Hierarchy ◽  
Design Elements ◽  
Packaging Design ◽  
Shannon's Entropy ◽  
Hierarchy Process

Starch is a natural polymer and eligible for short-term, single-use food packaging applications. Nevertheless, different starches have different features and properties determined by their botanical plant origins. This paper presents an approach that combines Shannon’s entropy and the Analytic Hierarchy Process method to aid the selection process of starch as matrix in green biocomposites for takeout food packaging design. The proposed selection system ranks alternative starches in terms of the key design elements, i.e. strength, barrier property, weight, and cost. Shannon’s entropy established corresponding weight values for the indicators selected. Six starches: wheat, maize, potato, cassava, sago, and rice were appraised using gathered data from the literature to determine their suitability as a more sustainable option. This study found that sago starch obtained the highest priority score of 26.8%, followed by rice starch (20.2%). Sensitivity analysis was then carried out to further verify the results; sago starch was at the top rank for five of six different scenarios tested. The results showed that sago starch is the starch that can best satisfy the design requirements. Despite the results attained, the selection framework used could be enhanced with a more comprehensive attributes assessment and extensive dataset.

scholarly journals Refractured Well Selection for Multicriteria Group Decision Making by Integrating Fuzzy AHP with Fuzzy TOPSIS Based on Interval-Typed Fuzzy Numbers

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Tiejun Li ◽  
Jianhua Jin ◽  
Chunquan Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Fuzzy Numbers ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Fuzzy Topsis ◽  
Selection Problem ◽  
Triangular Fuzzy Numbers ◽  
Analytic Hierarchy ◽  
Multicriteria Group Decision Making

Multicriteria group decision making (MCGDM) research has rapidly been developed and become a hot topic for solving complex decision problems. Because of incomplete or non-obtainable information, the refractured well-selection problem often exists in complex and vague conditions that the relative importance of the criteria and the impacts of the alternatives on these criteria are difficult to determine precisely. This paper presents a new model for MCGDM by integrating fuzzy analytic hierarchy process (AHP) with fuzzy TOPSIS based on interval-typed fuzzy numbers, to help group decision makers for well-selection during refracturing treatment. The fuzzy AHP is used to analyze the structure of the selection problem and to determine weights of the criteria with triangular fuzzy numbers, and fuzzy TOPSIS with interval-typed triangular fuzzy numbers is proposed to determine final ranking for all the alternatives. Furthermore, the algorithm allows finding the best alternatives. The feasibility of the proposed methodology is also demonstrated by the application of refractured well-selection problem and the method will provide a more effective decision-making tool for MCGDM problems.

scholarly journals Development of autopoietic economic structures in the Baltic states: analysis of factors

Equilibrium ◽  
2017 ◽  
Vol 12 (2) ◽  
pp. 319
Author(s):  
Mangirdas Morkunas ◽  
Viktorija Skvarciany ◽  
Jelena Titko
Keyword(s):  
Fuzzy Numbers ◽  
Value Added ◽  
Baltic States ◽  
Analytic Hierarchy ◽  
Factors Affecting ◽  
Business System ◽  
Business Structures ◽  
The Baltic ◽  
Open Markets ◽  
Hierarchy Process

Research background: Since the introduction of the concept in 1972 Autopoiesis has enjoyed great popularity among academicians representing various fields of science. However, the number of studies devoted to the investigation of factors that have an impact on the formation of autopoietic economic structures is quite limited. This paper addresses the gap in scientific research on autopoiesis of economic structures in small open markets, specifically in the Baltic States.Purpose of the article: The paper aims to identify and evaluate factors that turn on self-organization mechanisms of autopoietic economic structures in the Baltic States, in particular in Latvia.Methods: Expert survey was used to identify the most important factors affecting the for-mation of meso-economic entities in the Baltic States. The factors’ assessments provided by seven experts were analyzed. Analytic Hierarchy Process (AHP) with fuzzy numbers was employed to process the data. Two different scales of evaluation (inverse linear and balanced) were used.Findings & Value added: The factors influencing the process of formation of business groups were evaluated by experts. Research results allow for making conclusions regarding the causes of the business integration, and impact of diversified integrated business structures on the country's business system in Central Europe.

scholarly journals A Global & Environmental Coral Analysis System with SPA-Based Semantic Computing for Integrating and Visualizing Ocean-Phenomena with “5-Dimensional World-Map”

2020 ◽  
Author(s):  
Yasushi Kiyoki ◽  
Petchporn Chawakitchareon ◽  
Sompop Rungsupa ◽  
Xing Chen ◽  
Kittiya Samlansin
Keyword(s):  
Knowledge Base ◽  
Semantic Space ◽  
Semantic Interpretation ◽  
Health Level ◽  
Global Environmental ◽  
Coral Health ◽  
Ocean Environment ◽  
Computing Method ◽  
Level Analysis ◽  
Semantic Computing

Semantic computing is essentially significant for realizing the semantic interpretation of natural and social phenomena and analyzes the changes of various environmental situations. The 5D World Map (5DWM) System [4,6,8] has introduced the concept of “SPA (Sensing, Processing and Analytical Actuation Functions)” for global environmental system integrations [1–4], as a global environmental knowledge sharing, analysis and integration system. Environmental knowledge base creation with 5D World Map is realized for sharing, analyzing and visualizing various information resources to the map which can facilitate global phenomena-observations and knowledge discoveries with multi-dimensional axis control mechanisms. The 5DWM is globally utilized as a Global Environmental Semantic Computing System, in SDGs 9, 11, 14, United-Nations-ESCAP: (https://sdghelpdesk.unescap.org/toolboxes) for observing and analyzing disaster, natural phenomena, ocean-water situations with local and global multimedia data resources. This paper proposes a new semantic computing method as an important approach to semantic analysis for various environmental phenomena and changes in a real world. This method realizes “Self-Contained-Knowledge-Base-Image” & “Contextual-Semantic-Interpretation” as a new concept of “Coral-Health-level Analysis in Semantic-Space for Ocean-environment” for global ocean-environmental analysis [8,9,12,18]. This computing method is applied to automatic database creation with coral-health-level analysis sensors for interpreting environmental phenomena and changes occurring in the oceans in the world. We have focused on an experimental study for creating “Coral-Health-level Analysis Semantic-Space for Ocean-environment” [8,9,12,18]. This method realizes new semantic interpretation for coral health-level with “coral-images and coral-health-level knowledge-chart”.

scholarly journals Application of multiple criteria decision methods to optimise learning scenarios

2016 ◽  
Vol 57 ◽  
Author(s):  
Julija Kurilova ◽  
Eugenijus Kurilovas
Keyword(s):  
Comparative Analysis ◽  
Quality Evaluation ◽  
Fuzzy Numbers ◽  
Analytic Hierarchy ◽  
Personalised Learning ◽  
Decision Methods ◽  
Learning Scenarios ◽  
Optimisation Methods ◽  
Hierarchy Process

In the paper, learning scenarios (units) quality evaluation and optimisation problems are analysed. Learning scenarios optimisation is referred here as its personalisation according to learners needs. In the paper, comparative analysis of two popular optimisation methods based on Fuzzy numbers theory and Analytic Hierarchy Process is performed, aiming to measure what method is the most suitable to evaluate the quality of personalised learning scenarios. Learning scenarios quality is referred here as its suitability to learners needs. Research results show that Fuzzy numbers theorybased methods are more suitable to evaluate the quality of personalised learning scenarios.

A New Reliability Allocation Method for Machine Tools Using the Intuitionistic Trapezoidal Fuzzy Numbers and TOPSIS

2021 ◽  
Author(s):  
Qiang Cheng ◽  
Chang Wang ◽  
Dongyang Sun ◽  
Hongyan Chu ◽  
Wenfen Chang
Keyword(s):  
Machine Tools ◽  
Fuzzy Numbers ◽  
Cnc Machine ◽  
Analytic Hierarchy ◽  
Reliability Allocation ◽  
Trapezoidal Fuzzy Numbers ◽  
Sorting Technique ◽  
Ideal Solutions ◽  
Multi Attribute Decision Making ◽  
And Performance

Abstract The reliability allocation of machine tools which is a multi-attribute decision making problem has great significance in designment of machine tools. This paper integrates the intuitionistic trapezoidal fuzzy numbers and performance sorting technique based on similar ideal solutions to achieve the flexible allocation of machine tools reliability. Firstly, intuitionistic trapezoidal fuzzy numbers are employed to integrate decisions made by multiple decision makers and fuzzy information of their preferences. Then, intuitionistic trapezoid fuzzy numbers’ expectations are treated as the weights of criteria. Finally, performance sorting technique based on similar ideal solutions is used to obtain the reliability allocation weight of every subsystem. To investigate the efficacy and simplicity of the provided approach, reliability distribution in a CNC machine tool is introduced as an example to explain its specific contents. It can be concluded that the provided method is more precise and convenient by comparing the results of this approach with those obtained by analytic hierarchy process method.

Fuzzy Ratings in Mechanical Engineering Design—Application to Bearing Selection

1996 ◽  
Vol 210 (1) ◽  
pp. 49-53 ◽  
Author(s):  
Y H Chen
Keyword(s):  
Engineering Design ◽  
Design Automation ◽  
Fuzzy Numbers ◽  
Weighted Average ◽  
Design Stage ◽  
Design Elements ◽  
Fuzzy Weighted Average ◽  
Design Alternatives ◽  
Abstract Level

In the preliminary stage of engineering design, descriptions of design elements are often imprecise. In this paper, imprecision is represented using fuzzy numbers. Calculation based on fuzzy weighted average is performed to produce the ratings among design alternatives. Alternatives then proceed to the more detailed design stage in the fuzzy rating order. This method provides a tool for design automation at a higher abstract level. This is demonstrated in the bearing selection case study where imprecise linguistic description of a design problem in a manner similar to human language can be accommodated.

A personalized recommendation model for online apparel shopping based on Kansei engineering

2017 ◽  
Vol 29 (1) ◽  
pp. 2-13 ◽  
Author(s):  
Xiaoxi Zhou ◽  
Hui’e Liang ◽  
Zhiya Dong
Keyword(s):  
Online Shopping ◽  
Asia Pacific ◽  
Personalized Recommendation ◽  
Kansei Engineering ◽  
Emotional Needs ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Design Elements ◽  
Apparel Shopping ◽  
User Ratings

Purpose Today clothing has become the largest category in online shopping in China, and even in Asia-Pacific. The satisfaction degree of apparel online shopping can be improved by effective personalized recommendation. The purpose of this paper is to propose a personalized recommendation model and algorithm based on Kansei engineering, traditional filtering algorithm and the knowledge relating to apparel. Design/methodology/approach Users’ perceptual image and the design elements of apparel based on Kansei engineering are discussed to build the mapping relation between the design elements and user ratings employing verbal protocol, semantic differential and partial least squares. The implicit knowledge and emotional needs pertaining to users are accessed using analytic hierarchy process. A personalized recommendation model for apparel online shopping is established and the algorithm for the personalized recommendation process is proposed. To present the personalized recommendation model, men’s plaid shirts are taken as the example, and the recommendations of apparel for online shopping were implemented and ranked in the context of differing users’ emotional needs. A comparison between the traditional model and this model is made to verify the effectiveness. Findings The recommendation model is capable of analyzing data and information effectively, and providing fast, personalized apparel recommendation services in accordance with users’ emotional needs. The experimental results suggest that the model is effective. Originality/value Similar researches of recommendation mainly focus on the field of computer science, the basic idea of which is using users’ history accessing records or the preferences of other similar users for determination of users’ preferences. Since the attributes of apparel products are not factored in the approach referred above, the issue of personalized recommendation cannot be solved in a really effective way. Combining Kansei engineering and recommendation algorithm, a framework for apparel product recommendation is presented and it is a new way for improvement of recommendations for apparel products on shopping sites.

scholarly journals APPLICATION OF FUZZY AHP FOR RANKING AND SELECTION OF ALTERNATIVES IN CONSTRUCTION PROJECT MANAGEMENT

2017 ◽  
Vol 23 (8) ◽  
pp. 1123-1135 ◽  
Author(s):  
Natasa PRASCEVIC ◽  
Zivojin PRASCEVIC
Keyword(s):  
Project Management ◽  
Construction Projects ◽  
Fuzzy Numbers ◽  
Fuzzy Ahp ◽  
Construction Project ◽  
Construction Project Management ◽  
Analytic Hierarchy ◽  
Fuzzy Mean ◽  
Ranking Of Alternatives ◽  
Fuzzy Weights

The construction project management (CPM) is very important and large segment of entire project manage­ment (PM). Realisation of construction projects is usually long term process which requests significant financial, mate­rial, human and other resources to fulfil contracted obligations and achieve a good quality of works. Therefore, making good decisions with the satisfaction of various criteria is one of the main conditions to achieve planed business objec­tives and finish the project in contracted time with good quality. This paper proposes a new procedure for determination of the weights of criteria and alternatives in the Fuzzy analytic hierarchy process (FAHP) with trapezoidal fuzzy number using a new method for finding eigenvelues and eigenvectors of the criteria and alternatives, which is based on expected values of the fuzzy numbers and their products. Local and global fuzzy weights of the alternatives are determined using linear programming. In the paper a formula for ranking fuzzy numbers by reduced generalized fuzzy mean is also pro­posed, since ranking by the coefficient of variation is not always reliable. In the presented case study, applying proposed method, from imprecise input data are obtained enough accurate and useful results for rational ranking of alternatives related to the project realization.

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