Investigation of Robotics Technology Based on Bipolar Complex Intuitionistic Fuzzy Soft Relation

Gwak, Jeonghwan; Garg, Harish; Jan, Naeem

doi:10.1007/s40815-023-01487-0

Cited by 14 publications

(3 citation statements)

References 42 publications

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“…In addition to time series and forecasting methods, are widely used in the field of medicine for clustering images and diagnostics 16 – 18 . Numerous studies employing IFSs have been proposed by Fan et al 19 , Kumar and Gangwar 20 , Lei, et al 21 , Tak 22 , Gwak et al 23 .…”

Section: Introductionmentioning

confidence: 99%

An adaptive categorical effect size method based on intuitionistic meta fuzzy functions

Yabacı Tak

2023

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There are several categorical effect size methods in the literature. It is not clear which method performs better for a given dataset and it is a challenging task to select the correct method for a given dataset. In this sense, to overcome the questions like “Which method should we choose?” and “Which categorical effect size method is more reliable for a given dataset?”, an adaptive categorical effect size method based on intuitionistic meta fuzzy functions is introduced in the paper. Thus, the main motivation of the proposed method is to obtain more accurate outcomes by combining the results of better performing methods instead of relying on only one method. In the study, the intuitionistic fuzzy c-means clustering algorithm is adapted to meta fuzzy functions by incorporating not only membership degrees but also non-membership degrees to improve the clustering accuracy of meta fuzzy functions. Meta fuzzy functions are the linear combination of seven categorical effect size methods and the weights, which are calculated from membership grades from intuitionistic fuzzy c-means algorithm. Among the functions, the one with the lowest mean absolute percentage error is selected as the best. To evaluate the performance of the proposed method, 2 × 3, 2 × 4, and 3 × 4 contingency tables were simulated. Additionally, the performance of the proposed method is also assessed by applying it to a real-time dataset. Experimental results show that the proposed method outperforms compared to the evaluated seven categorical effect size methods in terms of mean absolute percentage error. Also, the calculated effect sizes are within the range of ±10% in terms of bias. Thus, the results verified that proposed method achieves greater reliability.

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Section: Introductionmentioning

confidence: 99%

An adaptive categorical effect size method based on intuitionistic meta fuzzy functions

Yabacı Tak

2023

Sci Rep

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“…In a fuzzy system, the knowledge given by human experts is modeled through if-then rules from which the system can infer a valid result despite natural language uncertainty [2]. The application of a Fuzzy Inference System (FIS) in many fields, such as control [3], modeling [4], classification [5][6][7], energy [8], health [9], among others [10][11][12] has encouraged the search for developmental tools capable of providing facilities for the design, simulation, and implementation of fuzzy systems to either standard processor or specific hardware devices. Most of the available software tools for the design of FISs are developed by the scientific community and are open source, some of them are FISDeT [13], fuzzycreator [14], FisPro [15], jFuzzyLogic [16], and JUZZY Online [17], which is an online toolkit.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Hardware Tool: An Adaptable Tool to Facilitate the Implementation of Fuzzy Inference Systems in Hardware

2023

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A Fuzzy Inference System (FIS) is a system that represents human reasoning based on fuzzy if-then rules to extract valid results from imprecise or uncertain information. These systems have been applied to various engineering fields, such as control and image recognition, and have encouraged the search for development tools that provide facilities for the design, simulation, and implementation of FISs. Most of the available software tools for the design of FISs have been developed by the scientific community, and very few are commercial tools. According to the state of the technology, the fuzzy systems implemented in hardware have shown higher performance than software implementations. For this reason, different strategies for automatic hardware synthesis of FISs have been proposed in the literature. The available tools for FIS implementation, including MATLAB, Simulink, and Xfuzzy environment, require advanced hardware knowledge, and it is necessary to synthesize and implement the program on FPGA each time a change is made to the code. This paper presents a novel approach for the implementation of fuzzy systems on hardware devices that enables the direct implementation of FISs through a graphical user interface. The VHDL code is pre-synthesized and integrated with the interface, allowing users to experiment with different input parameters, such as membership functions and fuzzy rules, without resynthesizing the code on an FPGA. To verify the effectiveness of the proposed approach, experiments were conducted on two similar System-on-Chip (SoC) devices, VEEK-MT and VEEK-MT2. The results showed that the proposed solution represents a significant advancement in the study of fuzzy systems on hardware devices, providing a flexible and user-friendly approach to their design and implementation.

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“…Its influencing factors are characterized by complexity, fuzziness, and uncertainty. The expression of evaluation indexes has mixed multi-attribute characteristics such as crisp value, interval type [15], and linguistic. The evaluation model focuses on system theory and prediction theory and establishes mathematical models and methods to explore the differences of regional geological environment from the perspective of sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Geo-Environment Carrying Capacity Based on Intuitionistic Fuzzy TOPSIS Method: A Case Study of China

et al. 2023

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The resource environment is a fundamental prerequisite for the construction of ecological civilization and the realization of sustainable development goals. It is also a core guarantee for human production activities. Conducting an evaluation of regional geo-environmental carrying capacity has significant practical importance for achieving sustainable development in the region. However, the existing evaluation methods for geo-environmental carrying capacity fail to effectively integrate multi-source data, resulting in an incomplete reflection of the level of regional geological carrying capacity. To address this issue, this study introduces the intuitionistic fuzzy multi-attribute decision-making method into the geo-environmental carrying capacity evaluation, according to the unique topographic and geomorphological characteristics of the region. A complete analysis framework is established, which integrates the intuitionistic fuzzy and TOPSIS models to classify the geo-environmental carrying capacity evaluation into five grades: high, relatively high, medium, relatively poor, and poor. Using Meishan, China as an example, the region is divided into 33 geomorphological units based on its geographical features. The results show that: (a) the percentage of natural units with high carrying capacity is 17.27%, that of relatively high natural units is 14.07%, that of medium natural units is 31.70%, that of relatively poor natural units is 27.51%, and that of poor natural units is 9.45%; (b) the geo-environmental carrying capacity exhibits spatial differences and uneven distribution. Furthermore, the average annual rainfall and degree of karst development are the main factors affecting the geo-environmental carrying capacity. These research results and findings can provide technical support for urban planning, regional sustainable development, and ecological environmental protection.

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Investigation of Robotics Technology Based on Bipolar Complex Intuitionistic Fuzzy Soft Relation

Cited by 14 publications

References 42 publications

An adaptive categorical effect size method based on intuitionistic meta fuzzy functions

An adaptive categorical effect size method based on intuitionistic meta fuzzy functions

Fuzzy Hardware Tool: An Adaptable Tool to Facilitate the Implementation of Fuzzy Inference Systems in Hardware

Evaluation of Geo-Environment Carrying Capacity Based on Intuitionistic Fuzzy TOPSIS Method: A Case Study of China

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