Adaptation of Induced Fuzzy Cognitive Maps to the Problems Faced by the Power Loom Workers

Narayanamoorthy, Samayan; Kalaiselvan, Samayan

doi:10.5815/ijisa.2012.09.10

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…Narayanamoorthy et al, [9] obtained maximum age group of endosulfan pesticide victims in Kerela using fuzzy combined effect time dependent-data-matrix. Kokila [10] worked on student's information gathering attitude by applying fuzzy matrix combined effect time dependent data matrix. Jon Arockiaraj and Murali [11] reported that the using fuzzy matrix analysis of seasonal fishing in Cuddalore.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity

R¹,

Patrick²,

RL³

et al. 2023

Int. J. Stat. Appl. Math.

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Fuzzy logic can be used to analyse and classify flora and faunal diversity. It uses fuzzy logic to describe richness and complexity of plant and animal life. Fuzzy logic can identify patterns in data to better understand diversity of an ecosystem. This study used a fuzzy combined effect time quantity dependent data matrix to predict the distribution and diversity of phytal fauna in Erayumanthurai coast. The method involved the use of Initial Raw Data Matrix (IRDM), Average Quantity Dependent Data Matrix (AQDM), Refined Quantity Dependent Data Matrices (RQDMs) and Combined Effect Quantity Dependent Data Matrix (CEQDM). Results showed that the high number of fauna was recorded in sites at α = 0.75 level and the faunal ranges were medium at α = 0.5 level. Negative values in the sites of S2, S3, and S4 indicated that faunal composition in these sites was not preferred. This fuzzy combined effect time quantity dependent data matrix was able to predict the exact place that had more anthropogenic disturbance to disturb the diversity and distribution of phytal fauna.

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Section: Introductionmentioning

confidence: 99%

Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity

R¹,

Patrick²,

RL³

et al. 2023

Int. J. Stat. Appl. Math.

View full text Add to dashboard Cite

show abstract

“…Similarly, Narayanamoorthy et al [12] used a fuzzy combined effect time dependent data matrix to estimate the maximum age group of endosulfan pesticide victims in Kerela. Kokila [13] used a fuzzy matrix combined effect time dependent data matrix to study student's information gathering attitudes. Jon Arockiaraj and Murali [14] reported that a fuzzy matrix analysis was used to analyze seasonal fishing in Cuddalore.…”

Section: Introductionmentioning

confidence: 99%

Exploring ant diversity with fuzzy logic and python

R¹,

Patrick²,

Vinolin³

et al. 2023

J. Math. Prob. Equations Stat.

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Fuzzy logic can be used to identify patterns in the data, which can be used to better understand the diversity of a particular ecosystem. This study examines the diversity of ants in different sites of Palayamkottai using the Combined Effect Quantity Dependent Data Matrix (CEQD-Matrix). Initial raw data is collected and transformed into an Average Quantity Dependent Data matrix (AQD Matrix) by taking ants' names as rows and point count sites as columns. A defined quantity dependent data matrix (RQD Matrix) is then generated using mean and standard deviation methods. Finally, a Combined Effect Quantity Dependent Data matrix (CEQD Matrix) is produced to show the cumulative effect of all the entries. Python is used to generate the graphs of the RQD Matrix and CEQD Matrix. It was found that the species Tetraponera rufonigra predominantly occupied the all sites, followed by Oecophylla smaragdina. The matrix was also used to predict the effects of anthropogenic disturbances on the ant diversity.

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“…Narayanamoorthy [11] estimated the maximum age group of silk weaver as bounded labours using fuzzy combined effect time dependent data matrix. Narayanamoorthy et al, [12] obtained maximum age group of endosulfan pesticide victims in Kerela using fuzzy combined effect time dependent-data-matrix. Kokila [13] worked on student's information gathering attitude by applying fuzzy matrix combined effect time dependent data matrix.…”

Section: Introductionmentioning

confidence: 99%

Assessing avian biodiversity in Swamithoppu saltpan with the fuzzy matrix approach

R¹,

Patrick²,

Jude³

et al. 2023

J. Math. Prob. Equations Stat.

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Fuzzy matrix is an invaluable tool in determining the biodiversity of a particular area. It is used to measure the species richness and abundance of a given area, as well as account for the presence of rare species. This study used fuzzy matrix analysis Initial Raw Data Matrix (IRDM), Average Quantity Dependent Data Matrix (AQDM), Refined Quantity Dependent Data Matrices (RQDMs), and Combined Effect Quantity Dependent Data Matrix (CEQDM) to determine the distribution and diversity of wetland birds in Samythoopu. The results showed that the maximum number of birds chose the sites of J1, J2,J3, S4, and S5, while the S2 point was identified as the most disturbed site and the birds were facing threats in sites including J4, S2, S3, S5, U1, U2, and U3. This fuzzy matrix can help predict the exact places with more anthropogenic disturbance to disturb the diversity and distribution of wetland birds.

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Adaptation of Induced Fuzzy Cognitive Maps to the Problems Faced by the Power Loom Workers

Cited by 10 publications

References 8 publications

Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity

Fuzzy combined effect time quantity dependent data matrix for predicting phytal fauna distribution and diversity

Exploring ant diversity with fuzzy logic and python

Assessing avian biodiversity in Swamithoppu saltpan with the fuzzy matrix approach

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