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Papers by Dr.S.Radhimeenakshi CS

Research paper thumbnail of Licensed Under Creative Commons Attribution CC BY Particle Swarm Optimization- A Review on Algorithmic Rule, Application and Scope

Abstract: Particle swarm optimization is a population-based, meta-heuristic optimization techniqu... more Abstract: Particle swarm optimization is a population-based, meta-heuristic optimization technique based on intelligence of swarm. The research on flock of birds or fish has been the motivation for this algorithm. Since this algorithm is easy to implement and requires few particles for tuning, this has been used widely nowadays. The main idea of this paper is to present the principle of PSO, improved PSO and research situation and the scope of future research.

Research paper thumbnail of Particle Swarm Optimization- A Review on Algorithmic Rule, Application and Scope

Particle swarm optimization is a population-based, meta-heuristic optimization technique based on... more Particle swarm optimization is a population-based, meta-heuristic optimization technique based on intelligence of swarm. The research on flock of birds or fish has been the motivation for this algorithm. Since this algorithm is easy to implement and requires few particles for tuning, this has been used widely nowadays. The main idea of this paper is to present the principle of PSO, improved PSO and research situation and the scope of future research.

Research paper thumbnail of Heart Failure Prediction Using Particle Swarm Optimization In Case Of Remote Health Monitoring

Heart failure is one of the major cardio-vascular diseases affecting the middle-aged and the aged... more Heart failure is one of the major cardio-vascular diseases affecting the middle-aged and the aged. It occurs due to decreased cardiac output. It can be both right-sided and left-sided failure of heart. This research paper proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementation is carried out using Java. The metrics such as time complexity and prediction accuracy are taken into account for the performance evaluation of the PSO for the prediction of heart failure. Simulation result output shows the performance improvement of the proposed method.

Research paper thumbnail of A Study on Prediction of Cardiovascular Victimization Data Processing Techniques

Heart disease term is related to several medical conditions of heart. Heart disease is one of the... more Heart disease term is related to several medical conditions of heart. Heart disease is one of the major health problems in India. The medical conditions refer to the abnormal health conditions that affect the heart. This paper presents a literature review of various data mining techniques implemented in prediction of heart disease. The observations reveal that neural networks and decision tree has more performance than all other data mining techniques.

Research paper thumbnail of Prediction of Heart Disease using Neural Network with Back Propagation

International Journal of Data Mining Techniques and Applications, 2015

several tools, software and algorithms are proposed by the researchers to develop effective medic... more several tools, software and algorithms are proposed by the researchers to develop effective medical decision support systems. New software, algorithms and tools are continuously emerging and upgraded depending on the real time situations. Detecting the heart disease is one of the major issues and it is investigated by many researchers. They have developed many intelligent DSS to improve the diagnosis of medical practitioners. Neural network is one among the tools to predict the heart disease. In this research paper, prediction of heart disease using Neural Network is presented. The proposed system used 13 attributes plus 2 additional attributes obesity and smoking for the heart disease prediction. The experiments conducted have shown a good performance.

Research paper thumbnail of Evaluating the Prediction of Heart Failure towards Health Monitoring using Particle Swarm Optimization

Research Journal of Applied Sciences, Engineering and Technology, 2014

Heart failure is one of the real cardio-vascular ailments influencing the center matured and the ... more Heart failure is one of the real cardio-vascular ailments influencing the center matured and the matured. It happens because of diminished cardiovascular yield. It can be both right-sided and left-sided failure of heart. This research study proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementation is carried out using java. The metrics such as time complexity and prediction accuracy are taken into account for the performance evaluation of the PSO for the prediction of heart failure. Simulation result outputs show the performance improvement of the proposed method.

Research paper thumbnail of Remote Heart Risk Monitoring System based on Efficient Neural Network and Evolutionary Algorithm

Indian Journal of Science and Technology, 2015

Objective: The objective of this paper is to predict the risk level of Heart Disease by applying ... more Objective: The objective of this paper is to predict the risk level of Heart Disease by applying Probabilistic Neural Network trained with Particle Swarm Optimization in case of Remote Health Monitoring. Methods: In order to achieve the aim of the activity, we propose hybrid model of Particle Swarm Optimization (PSO) and Probabilistic Neural Network (PNN). PSO is a population based meta-heuristic Evolutionary Algorithm (EA) whose goal is to explore the search space in order to find near-optimal solutions for feature selection. The optimal features selected can be used for prediction system to develop a classification model using probabilistic Neural Network. Results: First, we quantify the clinical data set from the UCI machine learning repository and measured the complexity. There are 13 attributes are used such as the age which identifies the age of the person, chest pain type has 4 values, serum cholesterol level, blood sugar, resting ECG results, serum cholesterol level, amount of heart rate achieved, x old peak, number of major vessels colored by fluoroscopy, slope of the peak exercise ST segment, thal, sex, height, weight and additional factor smoking. It has been shown that the time complexity of hybridizing PSO and PNN obtained the promising results compared to other two algorithms such as regression tree and PSO optimization. We also proposed the data mining process to deal with complexity, missing values and high dimensionality followed by incorporating the data mining functionalities like characterization, discrimination, association, classification, prediction and evolution analysis. The experiment carried out in Java on stat log heart disease data set performs better in all noise conditions. Conclusion: The performance was evaluated in terms of time complexity, accuracy, sensitivity and specificity and it proved that the hybrid model of PSO and PNN outperformed the Regression tree and PSO.

Research paper thumbnail of A Machine Learning Approach for Understanding Gpa with Students’ Experience Using Hybrid Algorithm

International Journal of Engineering Technologies and Management Research, 2020

Foreseeing understudies' review has risen as a noteworthy zone of examination in training bec... more Foreseeing understudies' review has risen as a noteworthy zone of examination in training because of the craving to distinguish the fundamental factors that impact scholastic execution. Due to constrained accomplishment in foreseeing the Grade Point Average (GPA), the greater part of the earlier research has concentrated on anticipating grades in a particular arrangement of classes dependent on understudies' earlier exhibitions. The issues related with information driven models of GPA expectation are additionally opened up by a little example measure and a generally vast dimensionality of perceptions in an analysis. In this paper, we use the best in class machine learning systems to develop and approve a prescient model of GPA exclusively dependent on an arrangement of self-administrative learning practices decided in a moderately little example analyze. At last, the objective of level expectation in comparative examinations is to utilize the built models for the outline of ...

Research paper thumbnail of Licensed Under Creative Commons Attribution CC BY Particle Swarm Optimization- A Review on Algorithmic Rule, Application and Scope

Abstract: Particle swarm optimization is a population-based, meta-heuristic optimization techniqu... more Abstract: Particle swarm optimization is a population-based, meta-heuristic optimization technique based on intelligence of swarm. The research on flock of birds or fish has been the motivation for this algorithm. Since this algorithm is easy to implement and requires few particles for tuning, this has been used widely nowadays. The main idea of this paper is to present the principle of PSO, improved PSO and research situation and the scope of future research.

Research paper thumbnail of Particle Swarm Optimization- A Review on Algorithmic Rule, Application and Scope

Particle swarm optimization is a population-based, meta-heuristic optimization technique based on... more Particle swarm optimization is a population-based, meta-heuristic optimization technique based on intelligence of swarm. The research on flock of birds or fish has been the motivation for this algorithm. Since this algorithm is easy to implement and requires few particles for tuning, this has been used widely nowadays. The main idea of this paper is to present the principle of PSO, improved PSO and research situation and the scope of future research.

Research paper thumbnail of Heart Failure Prediction Using Particle Swarm Optimization In Case Of Remote Health Monitoring

Heart failure is one of the major cardio-vascular diseases affecting the middle-aged and the aged... more Heart failure is one of the major cardio-vascular diseases affecting the middle-aged and the aged. It occurs due to decreased cardiac output. It can be both right-sided and left-sided failure of heart. This research paper proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementation is carried out using Java. The metrics such as time complexity and prediction accuracy are taken into account for the performance evaluation of the PSO for the prediction of heart failure. Simulation result output shows the performance improvement of the proposed method.

Research paper thumbnail of A Study on Prediction of Cardiovascular Victimization Data Processing Techniques

Heart disease term is related to several medical conditions of heart. Heart disease is one of the... more Heart disease term is related to several medical conditions of heart. Heart disease is one of the major health problems in India. The medical conditions refer to the abnormal health conditions that affect the heart. This paper presents a literature review of various data mining techniques implemented in prediction of heart disease. The observations reveal that neural networks and decision tree has more performance than all other data mining techniques.

Research paper thumbnail of Prediction of Heart Disease using Neural Network with Back Propagation

International Journal of Data Mining Techniques and Applications, 2015

several tools, software and algorithms are proposed by the researchers to develop effective medic... more several tools, software and algorithms are proposed by the researchers to develop effective medical decision support systems. New software, algorithms and tools are continuously emerging and upgraded depending on the real time situations. Detecting the heart disease is one of the major issues and it is investigated by many researchers. They have developed many intelligent DSS to improve the diagnosis of medical practitioners. Neural network is one among the tools to predict the heart disease. In this research paper, prediction of heart disease using Neural Network is presented. The proposed system used 13 attributes plus 2 additional attributes obesity and smoking for the heart disease prediction. The experiments conducted have shown a good performance.

Research paper thumbnail of Evaluating the Prediction of Heart Failure towards Health Monitoring using Particle Swarm Optimization

Research Journal of Applied Sciences, Engineering and Technology, 2014

Heart failure is one of the real cardio-vascular ailments influencing the center matured and the ... more Heart failure is one of the real cardio-vascular ailments influencing the center matured and the matured. It happens because of diminished cardiovascular yield. It can be both right-sided and left-sided failure of heart. This research study proposes a bio-inspired computing paradigm called particle swarm optimization shortly termed as PSO towards the prediction of heart failure. The implementation is carried out using java. The metrics such as time complexity and prediction accuracy are taken into account for the performance evaluation of the PSO for the prediction of heart failure. Simulation result outputs show the performance improvement of the proposed method.

Research paper thumbnail of Remote Heart Risk Monitoring System based on Efficient Neural Network and Evolutionary Algorithm

Indian Journal of Science and Technology, 2015

Objective: The objective of this paper is to predict the risk level of Heart Disease by applying ... more Objective: The objective of this paper is to predict the risk level of Heart Disease by applying Probabilistic Neural Network trained with Particle Swarm Optimization in case of Remote Health Monitoring. Methods: In order to achieve the aim of the activity, we propose hybrid model of Particle Swarm Optimization (PSO) and Probabilistic Neural Network (PNN). PSO is a population based meta-heuristic Evolutionary Algorithm (EA) whose goal is to explore the search space in order to find near-optimal solutions for feature selection. The optimal features selected can be used for prediction system to develop a classification model using probabilistic Neural Network. Results: First, we quantify the clinical data set from the UCI machine learning repository and measured the complexity. There are 13 attributes are used such as the age which identifies the age of the person, chest pain type has 4 values, serum cholesterol level, blood sugar, resting ECG results, serum cholesterol level, amount of heart rate achieved, x old peak, number of major vessels colored by fluoroscopy, slope of the peak exercise ST segment, thal, sex, height, weight and additional factor smoking. It has been shown that the time complexity of hybridizing PSO and PNN obtained the promising results compared to other two algorithms such as regression tree and PSO optimization. We also proposed the data mining process to deal with complexity, missing values and high dimensionality followed by incorporating the data mining functionalities like characterization, discrimination, association, classification, prediction and evolution analysis. The experiment carried out in Java on stat log heart disease data set performs better in all noise conditions. Conclusion: The performance was evaluated in terms of time complexity, accuracy, sensitivity and specificity and it proved that the hybrid model of PSO and PNN outperformed the Regression tree and PSO.

Research paper thumbnail of A Machine Learning Approach for Understanding Gpa with Students’ Experience Using Hybrid Algorithm

International Journal of Engineering Technologies and Management Research, 2020

Foreseeing understudies' review has risen as a noteworthy zone of examination in training bec... more Foreseeing understudies' review has risen as a noteworthy zone of examination in training because of the craving to distinguish the fundamental factors that impact scholastic execution. Due to constrained accomplishment in foreseeing the Grade Point Average (GPA), the greater part of the earlier research has concentrated on anticipating grades in a particular arrangement of classes dependent on understudies' earlier exhibitions. The issues related with information driven models of GPA expectation are additionally opened up by a little example measure and a generally vast dimensionality of perceptions in an analysis. In this paper, we use the best in class machine learning systems to develop and approve a prescient model of GPA exclusively dependent on an arrangement of self-administrative learning practices decided in a moderately little example analyze. At last, the objective of level expectation in comparative examinations is to utilize the built models for the outline of ...