Mohammed Kemal Ahmed, Durga Prasad Sharma, Hussein Seid Worku, Getinet Yima, Amir Ibrahim, T. B. Tufa
This study successfully designed and developed a smartphone application for livestock disease diagnosis, treatment, and reporting. The agile development framework Extreme Programming (XP) ensured efficient iteration and adaptation based on user feedback. Additionally, the integration of the Analytical Hierarchy Process (AHP) with veterinary expert input facilitated the prioritization of disease possibilities within the app. Furthermore, the application of Naive Bayes probability allowed the system to rank diseases based on them likelihood, enhancing the accuracy of diagnoses. Workshops, field observations, group discussions, and interviews with senior veterinary experts were used as data collecting and final product assessment tools to ensure it met the original criteria. Purposive sampling was used to distribute the application to 90 smartphone users who work in veterinary clinics, including 49 senior veterinary medicine students. The proposed system offers benefits such as improved healthcare access, early disease detection, enhanced disease management, and strengthened livestock health surveillance. This multifaceted approach holds significant promise for improving livestock health management, particularly in resource-limited settings.
{"title":"Leveraging Expert Knowledge for Mobile Livestock Care: Combining AHP and Naïve Bayes for Diagnosis, Treatment, and Management","authors":"Mohammed Kemal Ahmed, Durga Prasad Sharma, Hussein Seid Worku, Getinet Yima, Amir Ibrahim, T. B. Tufa","doi":"10.52783/cana.v31.856","DOIUrl":"https://doi.org/10.52783/cana.v31.856","url":null,"abstract":"This study successfully designed and developed a smartphone application for livestock disease diagnosis, treatment, and reporting. The agile development framework Extreme Programming (XP) ensured efficient iteration and adaptation based on user feedback. Additionally, the integration of the Analytical Hierarchy Process (AHP) with veterinary expert input facilitated the prioritization of disease possibilities within the app. Furthermore, the application of Naive Bayes probability allowed the system to rank diseases based on them likelihood, enhancing the accuracy of diagnoses. Workshops, field observations, group discussions, and interviews with senior veterinary experts were used as data collecting and final product assessment tools to ensure it met the original criteria. Purposive sampling was used to distribute the application to 90 smartphone users who work in veterinary clinics, including 49 senior veterinary medicine students. The proposed system offers benefits such as improved healthcare access, early disease detection, enhanced disease management, and strengthened livestock health surveillance. This multifaceted approach holds significant promise for improving livestock health management, particularly in resource-limited settings.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we study M/M/1 open queueing network with instantaneous Bernoulli feedback and preparatory work with three nodes when catastrophe occurs. We derive n number of customers in the system, queue length (all three nodes), system length and system time. The numerical examples are given to test the feasibility of the model.
本文研究了具有瞬时伯努利反馈的 M/M/1 开放式排队网络，以及灾难发生时三个节点的准备工作。我们推导出系统中的 n 个客户数、队列长度（所有三个节点）、系统长度和系统时间。我们给出了数值示例来检验模型的可行性。
{"title":"Study on M/M/1 Queueing Netwօrk with Preparatory Wօrk and Feeback using Three Nodes when Catastrophe Occurs","authors":"S. Shanmugasundaram","doi":"10.52783/cana.v31.853","DOIUrl":"https://doi.org/10.52783/cana.v31.853","url":null,"abstract":"In this paper we study M/M/1 open queueing network with instantaneous Bernoulli feedback and preparatory work with three nodes when catastrophe occurs. We derive n number of customers in the system, queue length (all three nodes), system length and system time. The numerical examples are given to test the feasibility of the model.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141673800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Introduction: This study uses a fuzzy-based methodology that combines agility score and certainty functions to assess the values of learning mathematics quickly. The paper emphasises the need of understanding the value of learning mathematics through tools like the Neutronosophic Agility Index in addition to discussing the usage of surveys to assess it. Objective: The aim of this study is to evaluate the values of learning mathematics’ agility by employing a fuzzy based methodology that integrates score and certainty functions. Finding out how agile the values are now and looking into ways to make them more agile are the objectives. Method: A paradigm for assessing the values of learning mathematical skills agility is established using a neutrosophic fuzzy method. The agility score is calculated to evaluate the level of agility. Additionally, the article recommends carrying out additional research using particular performance assessment standards. Result: The findings show that, according to its agility score, the benefit of knowing mathematics is "fairly agile". It implies the possibility of more progress by putting improvement recommendations into practice. It also emphasises the relationship between performance, agility, and organisational culture, underscoring the necessity for additional research employing a variety of fuzzy methodologies. Conclusion: In conclusion, the study is represented by agility scores corresponding to specific values. Self-confidence, with an agility score of 0.5377, ranks first, indicating reasonable confidence in decision-making. Perseverance (score: 0.5356) reflects resilience and determination. Decision-making (score: 0.5239) suggests a balanced approach. Tolerance (score: 0.5185) relates to handling diversity. Higher Order Thinking (score: 0.5166) involves cognitive abilities. The average agility score (0.5265) falls within the ‘Fairly Agile’ range. Enhancing these values can lead to higher agility categories.
{"title":"Modelling Neutrosophic Agility Index: A Mathematical Framework","authors":"M. Kavitha","doi":"10.52783/cana.v31.833","DOIUrl":"https://doi.org/10.52783/cana.v31.833","url":null,"abstract":"Introduction: This study uses a fuzzy-based methodology that combines agility score and certainty functions to assess the values of learning mathematics quickly. The paper emphasises the need of understanding the value of learning mathematics through tools like the Neutronosophic Agility Index in addition to discussing the usage of surveys to assess it.\u0000Objective: The aim of this study is to evaluate the values of learning mathematics’ agility by employing a fuzzy based methodology that integrates score and certainty functions. Finding out how agile the values are now and looking into ways to make them more agile are the objectives.\u0000Method: A paradigm for assessing the values of learning mathematical skills agility is established using a neutrosophic fuzzy method. The agility score is calculated to evaluate the level of agility. Additionally, the article recommends carrying out additional research using particular performance assessment standards.\u0000Result: The findings show that, according to its agility score, the benefit of knowing mathematics is \"fairly agile\". It implies the possibility of more progress by putting improvement recommendations into practice. It also emphasises the relationship between performance, agility, and organisational culture, underscoring the necessity for additional research employing a variety of fuzzy methodologies.\u0000Conclusion: In conclusion, the study is represented by agility scores corresponding to specific values. Self-confidence, with an agility score of 0.5377, ranks first, indicating reasonable confidence in decision-making. Perseverance (score: 0.5356) reflects resilience and determination. Decision-making (score: 0.5239) suggests a balanced approach. Tolerance (score: 0.5185) relates to handling diversity. Higher Order Thinking (score: 0.5166) involves cognitive abilities. The average agility score (0.5265) falls within the ‘Fairly Agile’ range. Enhancing these values can lead to higher agility categories.\u0000","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the treatment of glioblastomas, non-invasive methods for determining MGMT gene promoter methylation status are crucial due to their implications for chemotherapy responsiveness. This study utilizes a mathematical and computational framework to extract and analyze radiogenomic data from MRI images to predict the methylation status. The first step in our framework involves extracting radiogenomic data from MRI images. This process requires sophisticated image processing techniques to convert MRI scans into a format suitable for machine learning analysis. The features extracted include textural patterns, intensity distributions, and other relevant radiomic characteristics.To identify the most significant features, we employ a Random Forest (RF) algorithm. Mathematically, RF is an ensemble learning method that operates by constructing multiple decision trees during training and outputting the mode of the classes for classification tasks. The importance of each feature is evaluated based on its contribution to the accuracy of the model, quantified by metrics such as Gini impurity or information gain. Employing advanced machine learning models like VGG19, ResNet50, and Sequential FCNet Artificial Neural Networks, alongside traditional classifiers such as Naive Bayes and Logistic Regression, we analyze features identified by a Random Forest algorithm. Our mathematical approach ensures rigorous evaluation of model accuracy through sensitivity, specificity, and other performance metrics, presenting the Sequential FCNet ANN combined with ResNet50 as the superior model. This research contributes to the field of precision healthcare by enhancing the mathematical methods used in the non-invasive diagnosis of glioblastomas.
{"title":"Computational Predictions of MGMT Promoter Methylation in Gliomas: A Mathematical Radiogenomics Approach","authors":"Ayesha Agrawal, V. Maan","doi":"10.52783/cana.v31.844","DOIUrl":"https://doi.org/10.52783/cana.v31.844","url":null,"abstract":"In the treatment of glioblastomas, non-invasive methods for determining MGMT gene promoter methylation status are crucial due to their implications for chemotherapy responsiveness. This study utilizes a mathematical and computational framework to extract and analyze radiogenomic data from MRI images to predict the methylation status. The first step in our framework involves extracting radiogenomic data from MRI images. This process requires sophisticated image processing techniques to convert MRI scans into a format suitable for machine learning analysis. The features extracted include textural patterns, intensity distributions, and other relevant radiomic characteristics.To identify the most significant features, we employ a Random Forest (RF) algorithm. Mathematically, RF is an ensemble learning method that operates by constructing multiple decision trees during training and outputting the mode of the classes for classification tasks. The importance of each feature is evaluated based on its contribution to the accuracy of the model, quantified by metrics such as Gini impurity or information gain. Employing advanced machine learning models like VGG19, ResNet50, and Sequential FCNet Artificial Neural Networks, alongside traditional classifiers such as Naive Bayes and Logistic Regression, we analyze features identified by a Random Forest algorithm. Our mathematical approach ensures rigorous evaluation of model accuracy through sensitivity, specificity, and other performance metrics, presenting the Sequential FCNet ANN combined with ResNet50 as the superior model. This research contributes to the field of precision healthcare by enhancing the mathematical methods used in the non-invasive diagnosis of glioblastomas.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141677421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In order to identify mycosis fungoides in medical photos, the researchers used an algorithm. There are several procedures that the detection system needs to take in order to identify cell mycosis fungoides. Mycosis fungoides image features have been studied using the new fuzzy transform because of the function's significance in accurate stage analysis. The statistical properties that were taken into consideration were energy, homogeneity, contrast, correlation, median, mean, entropy, and homogeneity. It has been confirmed that these statistical traits may be used to differentiate across various mycosis fungoides time periods.. We relied on the persistence function since it provides more precise examination of affected regions. Orthogonal conversion was found to be effective in assessing pixel area without changing image properties, allowing for the diagnosis of various illness stages.
{"title":"Fuzzy S-Transform is used for Identifying Image Borders of the Medial Model Mycosic Fungoides","authors":"S. I. Al-Ali","doi":"10.52783/cana.v31.831","DOIUrl":"https://doi.org/10.52783/cana.v31.831","url":null,"abstract":"In order to identify mycosis fungoides in medical photos, the researchers used an algorithm. There are several procedures that the detection system needs to take in order to identify cell mycosis fungoides. Mycosis fungoides image features have been studied using the new fuzzy transform because of the function's significance in accurate stage analysis. The statistical properties that were taken into consideration were energy, homogeneity, contrast, correlation, median, mean, entropy, and homogeneity. It has been confirmed that these statistical traits may be used to differentiate across various mycosis fungoides time periods.. We relied on the persistence function since it provides more precise examination of affected regions. Orthogonal conversion was found to be effective in assessing pixel area without changing image properties, allowing for the diagnosis of various illness stages.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141675894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Our research meticulously navigates the realms of Fractional Quantum Mechanics (FQM), focusing on a critical examination of both numerical and analytical methods that harness the potential of fractional calculus to illuminate the quantum world's complexities. By embarking on this scholarly journey, we aim to decode the intricate dynamics that fractional equations reveal about quantum systems, pushing the boundaries of conventional quantum mechanics. This comparative study meticulously evaluates the efficacy and insights provided by these two distinct approaches, highlighting their contributions to a deeper understanding of quantum phenomena. As we traverse through the layers of quantum dynamics, our work seeks to contribute significantly to the theoretical framework of FQM, offering innovative perspectives and methodologies. The essence of this research lies in its potential to forge new theoretical pathways and inspire further exploration in the quantum domain, leveraging the unique capabilities of fractional calculus. By enriching the scientific community with our findings, we aspire to open new horizons in the study of quantum mechanics, marking a step forward in the ongoing quest to unravel the mysteries of the quantum universe.
{"title":"Numerical and Analytical Approaches to Fractional Quantum Mechanics","authors":"Vikas Kumar, Dr Nand Kumar","doi":"10.52783/cana.v31.936","DOIUrl":"https://doi.org/10.52783/cana.v31.936","url":null,"abstract":"Our research meticulously navigates the realms of Fractional Quantum Mechanics (FQM), focusing on a critical examination of both numerical and analytical methods that harness the potential of fractional calculus to illuminate the quantum world's complexities. By embarking on this scholarly journey, we aim to decode the intricate dynamics that fractional equations reveal about quantum systems, pushing the boundaries of conventional quantum mechanics. This comparative study meticulously evaluates the efficacy and insights provided by these two distinct approaches, highlighting their contributions to a deeper understanding of quantum phenomena. As we traverse through the layers of quantum dynamics, our work seeks to contribute significantly to the theoretical framework of FQM, offering innovative perspectives and methodologies. The essence of this research lies in its potential to forge new theoretical pathways and inspire further exploration in the quantum domain, leveraging the unique capabilities of fractional calculus. By enriching the scientific community with our findings, we aspire to open new horizons in the study of quantum mechanics, marking a step forward in the ongoing quest to unravel the mysteries of the quantum universe.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work aims to define a new class of sets in nano topological spaces called Nano (Nα) ̌- closed and (Nα) ̂-open sets, and to prove its verifiable properties and theorems.
{"title":"On GeneralizedNanoℕ?̌-Closed andNanoℕα̂-OpenSetsin Nano-Topological Spaces","authors":"Abdulaziz .S. Hameed","doi":"10.52783/cana.v31.858","DOIUrl":"https://doi.org/10.52783/cana.v31.858","url":null,"abstract":"This work aims to define a new class of sets in nano topological spaces called Nano (Nα) ̌- closed and (Nα) ̂-open sets, and to prove its verifiable properties and theorems.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":"161 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Intuitionistic fuzzy D-algebra introduces a novel framework extending classical fuzzy algebra by incorporating degrees of membership and non-membership. This approach addresses the inherent uncertainty and imprecision in real-world systems. Topological techniques facilitate the analysis of convergence and continuity properties, ensuring the robustness of mathematical models. The need for such a framework arises from the limitations of classical fuzzy algebra in capturing nuanced degrees of uncertainty. Real-world decision-making processes often involve complex, ambiguous information that cannot be adequately represented by binary membership functions alone. Intuitionistic fuzzy D-algebra offers a more nuanced representation, expressing hesitation and uncertainty inherent in decision-making contexts. The proposed work comprehensively explores intuitionistic fuzzy D-algebra, including the formal definition of core structures, mathematical modelling, validation strategies through examples and counterexamples, and the development of interactive visualizations. By integrating computational tools and theoretical insights, this framework provides a versatile platform for addressing uncertainty in various domains, from decision-making systems to artificial intelligence, thus paving the way for innovative solutions and improved decision outcomes. The results provide an immersive exploration into the intricacies of intuitionistic fuzzy D-algebra. From the transformation of fuzzy sets into topological spaces to the dynamic manipulation of algebraic operations, each visualization offers an intense dive into understanding uncertainty and imprecision. The visuals serve as powerful educational tools, enabling a profound grasp of complex mathematical concepts and their practical implications in decision-making systems and artificial intelligence.
{"title":"Theoretical Foundation, Topological Technique, and Decision-Making Application of Intuitionistic Fuzzy D-Algebra","authors":"M. Siva","doi":"10.52783/cana.v31.945","DOIUrl":"https://doi.org/10.52783/cana.v31.945","url":null,"abstract":"Intuitionistic fuzzy D-algebra introduces a novel framework extending classical fuzzy algebra by incorporating degrees of membership and non-membership. This approach addresses the inherent uncertainty and imprecision in real-world systems. Topological techniques facilitate the analysis of convergence and continuity properties, ensuring the robustness of mathematical models. The need for such a framework arises from the limitations of classical fuzzy algebra in capturing nuanced degrees of uncertainty. Real-world decision-making processes often involve complex, ambiguous information that cannot be adequately represented by binary membership functions alone. Intuitionistic fuzzy D-algebra offers a more nuanced representation, expressing hesitation and uncertainty inherent in decision-making contexts. The proposed work comprehensively explores intuitionistic fuzzy D-algebra, including the formal definition of core structures, mathematical modelling, validation strategies through examples and counterexamples, and the development of interactive visualizations. By integrating computational tools and theoretical insights, this framework provides a versatile platform for addressing uncertainty in various domains, from decision-making systems to artificial intelligence, thus paving the way for innovative solutions and improved decision outcomes. The results provide an immersive exploration into the intricacies of intuitionistic fuzzy D-algebra. From the transformation of fuzzy sets into topological spaces to the dynamic manipulation of algebraic operations, each visualization offers an intense dive into understanding uncertainty and imprecision. The visuals serve as powerful educational tools, enabling a profound grasp of complex mathematical concepts and their practical implications in decision-making systems and artificial intelligence.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a new continuous distribution family called the Alpha logarithm family, which is a new modelling strategy for fitting data subject to univariate continuous distributions. This is achieved by introducing an additional parameter for greater flexibility using a single-parameter Natural logarithm transformation which can enhance some of the modeling capabilities of some Parental Continuous Distributions: This technique was applied to the exponential distribution to obtain a new two-parameter distribution, and the changes that occurred in the exponential distribution were observed. The general properties and functions of the new distribution were also derived and studied, and the estimators of the two parameters were derived. The efficiency of the estimators is verified through the simulation study. The new distribution is also applied to two sets of real data to prove the benefit of the new transformation, and we show that the proposed model is better than the asymptotic distributions with which it was compared on the selected data.
{"title":"A New Family of Distributions with an Application to Exponentially Distribution","authors":"Layla Abdul, Jaleel Mohsin, Hazim Ghdhaib Kalt","doi":"10.52783/cana.v31.832","DOIUrl":"https://doi.org/10.52783/cana.v31.832","url":null,"abstract":"This paper introduces a new continuous distribution family called the Alpha logarithm family, which is a new modelling strategy for fitting data subject to univariate continuous distributions. This is achieved by introducing an additional parameter for greater flexibility using a single-parameter Natural logarithm transformation which can enhance some of the modeling capabilities of some Parental Continuous Distributions: This technique was applied to the exponential distribution to obtain a new two-parameter distribution, and the changes that occurred in the exponential distribution were observed. The general properties and functions of the new distribution were also derived and studied, and the estimators of the two parameters were derived. The efficiency of the estimators is verified through the simulation study. The new distribution is also applied to two sets of real data to prove the benefit of the new transformation, and we show that the proposed model is better than the asymptotic distributions with which it was compared on the selected data.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676665","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research work studies the optimization of intuitionistic fuzzy valued functions in unconstrained problems. The Interval Newton's Method using an Intuitionistic approach addresses both single and multivariable optimization problems. The study incorporates a mathematical comprehension of interval intuitionistic fuzzy valued problems, as well as real-world examples to demonstrate their effectiveness. Furthermore, MATLAB code is provided to demonstrate the implementation of the Interval Newton's Method.
{"title":"Solving Intuitionistic Fuzzy Unconstrained Optimization Problems Using Interval Newton’s Method","authors":"S. Shilpa, Ivin Emimal, R. Hepzibah","doi":"10.52783/cana.v31.835","DOIUrl":"https://doi.org/10.52783/cana.v31.835","url":null,"abstract":"This research work studies the optimization of intuitionistic fuzzy valued functions in unconstrained problems. The Interval Newton's Method using an Intuitionistic approach addresses both single and multivariable optimization problems. The study incorporates a mathematical comprehension of interval intuitionistic fuzzy valued problems, as well as real-world examples to demonstrate their effectiveness. Furthermore, MATLAB code is provided to demonstrate the implementation of the Interval Newton's Method.","PeriodicalId":40036,"journal":{"name":"Communications on Applied Nonlinear Analysis","volume":" 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141676783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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