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Papers by Amudha Vediappan

Recent Trends in Management and Commerce , 2022

The activity of walking through hilly country for pleasure. He is an avid athlete and loves mount... more The activity of walking through hilly country for pleasure. He is an avid athlete and loves mountain walking. Mountaineering is a terrifying quest used for mathematical optimization problems in the field of artificial intelligence. Given a large input and a good horistic function, it tries to find a good enough solution to the problem. The mountaineering algorithm consists of three parts, where the global maximum or optimal solution cannot be reached: the local maximum, the ridge and the plateau. The trek is not complete or optimal, the time complex of O (∞) but the space complex of O (b). There is no special processing data system as mountaineering rejects old nodes. Trekking in the Alps or other high mountains. This is not an efficient method. This does not apply to problems where the value of the horticultural function suddenly decreases while the solution is in view. First-choice trekking enables balanced trekking by randomly creating heirs until something better than the current situation develops. Whenever this is a good strategy there are many (e.g., thousands) heirs in a state. So the first preferred mountain climbing is a special type Random mountain climbing. Description. This is a robust mountaineering algorithm. A person is initiated approximately. ... When the individual reaches a local optimal state a new solution is created approximately and mountaineering begins again. The best first search is a traversal technique, which checks which node is the most reliable and decides which node to visit next by checking it. To this end, it uses the appraisal function to determine travel. Climbing is used to describe traditional 'siege' techniques, where you will climb the mountain several times before being driven to the summit. Albinism, on the other hand, focuses on 'fast and light' climbs. Free climbing was created to describe any style of climbing that is not AIDS related. ... In free climbing, the climber moves the wall under their own force without the use of any special gear (except for the climbing shoes) to help them move upwards. Climbers can only survive for a short time in the 'death zone' at 8000 m and above, where there are numerous challenges. Deep cracks, avalanches, cliffs and snowflakes make the high form of trekking a very dangerous endeavor. Caldwell and George's son use headlamps to illuminate their way, climbing at night when the temperature is cold-meaning their hands sweat less and there is more friction between their rubber shoes and granite. According to the author, climbing mountains is a very difficult task for people and they enjoy crossing obstacles. Mountaineering is neither complete nor optimal, the time complex of O (∞) but the space complex of O (b). There is no special processing data system as mountaineering rejects old nodes.

Recent trends in Management and Commerce, 2021

Mayfly algorithm (MA) is an optimal way to achieve this goal. It is a newly developed algorithm t... more Mayfly algorithm (MA) is an optimal way to achieve this goal. It is a newly developed algorithm that combines the key benefits of PSO, GA and FA, resulting in a hybrid of PSO-GA-FA. Compared with the other seven transformation methods, the performance evaluation performed using the CEC test operations demonstrates the dominance of MA in terms of accumulation rate and velocity. Although this requires rapid integration, it is not yet used in many engineering optimization fields, so we propose to use it for antenna optimization tasks. Predictions for the next century 15 to 95 Cm, the 50 cm 'best estimate' indicates a significant increase in sea level rise over the last century, with records from both the Atlantic and the Pacific in the Northern Hemisphere showing sea increase. However, in most cases, of some sites This condition is reduced due to surface resurfacing or regeneration. Rise is the height of the average level of the ocean surface and the increase in wavelength around it. The mayfly optimization algorithm (MOA) was proposed with a better hybridization of the particle swarm optimization (PSO) and the differential evolution (DE) algorithms. The velocity would be relevant to the Cartesian distance among the relevant individuals.

REST Publisher, 2021

Optional selection technique similar to The Ideal So lution (TOPSIS) is a mu lti-criterion decisi... more Optional selection technique similar to The Ideal So lution (TOPSIS) is a mu lti-criterion decision Is the method of analysis. This was originally Sing-Lai Hwang Created in 1981 by and Yoon, and Yoon and Yoon in 1987. In 1993Further improved by Hwang, Lai and Liu. Became TOPSIS Narrow geometric Distance from selected alternative positive optical solution (PIS) and negative ideal Based on the idea that the solution must have a very long geome tric distance (NIS) Consists of. Identify Weights for each criterion, each Every alternative and best alternative to the criteria Normalizing the marks and geometric distance between Compensation is a method of comparing the set of alternatives by calculation. The assumption of TOPSIS is The criteria increase uniformly or Decrease. Many because of parameters or Criteria scale problems often have Normalizat ion of inappropriate dimensions is common needed. Co mpensation systems such as TOPSIS Trade between criteria A llo w exchanges where bad results on one scale are good results on another scale May be denied by. It offers So much more than unpaid methods Realistic modeling form, in wh ich Alternative solutions are included or excluded In terms of tough cutoffs. Its in nuclear power plants an example of application given.

Data Analytics and Artificial Intelligence, 2021

In evolutionary calculat ion, differential evolution (DE) is a method of developing a problem in ... more In evolutionary calculat ion, differential evolution (DE) is a method of developing a problem in an evolutionary process. Such algorith ms do not make some or all assumptions about the basic optimization problem and can quickly exp lore very large design gaps. Differential Evolut ion (DE) is a co mp lete search algorith m based on population, which is based on a candidate' s evolutionary process. Improves the problem by repeatedly upgrading the solution. Such algorith ms give little or no speculation about the basic optimizat ion problem and will quickly exp lore the larger design gaps; both genetic algorith ms and differential evolution are examp les of evolutionary calculations. Genetic mechanis ms are very clo se to the metaphor of genetic reproduction. ... Different evolution is in the same style, but correspondence is not precise. DE is the processing of the population of individuals represented by the dimensional vectors of real numbers Is an evolutionary mec hanism. In every repetition, in every parent, a mutation is a different mutation driver Created by The mutant then communicates with the parents and gives the offspring a different evolution (DE) a co mpetitive fo rm of evolutionary mechanis ms. It relies heavily on modifying solutions, using measured differences of appro ximately selected indiv iduals fro m the population, to develop new solutions. Differential reproductive success refers to the statistical analysis that compares successful reproduction rat es between groups in a given generation of a speciesin other wo rds, how well each individual group is able to leave offspring, with examples of both genetic mechanisms and different evolution. Evo lutionary calcu lation. Genetic mechanis ms are very close to the metaphor of genetic reproduction. ... Different evolution is in the same style, but correspondence is not precise. DE is the processing of the population of individuals represented by the dimensional vectors of real numbers Is an evolutionary mechanis m. In each iteration, fo r each parent, one with a different mutation driver the mutant is created. The mutant then goes to the parents and gets an offspring

Books by Amudha Vediappan

REST Publisher, 2022

Gravitational search algorithm is a naturally occurring algorithm based on Newton's mathematical ... more Gravitational search algorithm is a naturally occurring algorithm based on Newton's mathematical model of the law of gravitation and motion. Over the course of a decade, researchers have provided many variants of the gravitational search algorithm by modifying its parameters to effectively solve complex optimization problems. This paper conducts a comparative analysis of ten types of gravity search algorithms that modify the three parameters of optimum, speed and position. Tests are conducted on two sets of benchmark types, namely standard functions and issues belonging to different types such as CEC2015 functions, univocal, multimodal and unrestricted optimization functions. Performance comparison is evaluated and statistically validated based on the average exercise value and concentration graph. In trials, IGSA has achieved excellent accuracy through a balanced trade between exploration and exploitation. Furthermore, three negative breast cancer datasets were considered to analyze the efficacy of GSA variants for the black section. Different performance analyzes were performed based on both quality and quantity with the integrated jacquard index as a performance measure. Tests confirm that the IGSA based method worked better than other methods.

REST Publisher, 2021

The complex proportional evaluation, COPRAS It is used. for multicriteria evaluation of both. max... more The complex proportional evaluation, COPRAS It is used. for multicriteria evaluation of both. maximizing and minimizing criteria values Complex proportional assessment is an analytical tool for solving multi-criteria decision making problems. ... it seems that the recommended framework of COPRaS-iviF can be satis-factorial implemented in decision making problems under ambiguous and ill-defined conditions. Complex Proportional Assessment (COPRAS) method by 1994 [84-87] by Javatskas, Kokluskas and Sarka Introduced. This method is used to increase and decrease the index values, and the result Increasing and decreasing the index of attributes in the evaluation The effect of is considered separately. For evaluating and ranking hotels Complex Proportional Assessment (COPRAS) model. Compatibility of the proposed structure an empirical example and real-world case study from the Indian tourism industry is provided to check. Finally, the validity of the proposed model Comparison to study character and strength And sensitivity analysis is performed. The diversity of different biases The tendencies of the various dependencies on which they are based are the same Not sampled, these complex algorithms Are identified and reported.

Recent Trends in Management and Commerce , 2022

The activity of walking through hilly country for pleasure. He is an avid athlete and loves mount... more The activity of walking through hilly country for pleasure. He is an avid athlete and loves mountain walking. Mountaineering is a terrifying quest used for mathematical optimization problems in the field of artificial intelligence. Given a large input and a good horistic function, it tries to find a good enough solution to the problem. The mountaineering algorithm consists of three parts, where the global maximum or optimal solution cannot be reached: the local maximum, the ridge and the plateau. The trek is not complete or optimal, the time complex of O (∞) but the space complex of O (b). There is no special processing data system as mountaineering rejects old nodes. Trekking in the Alps or other high mountains. This is not an efficient method. This does not apply to problems where the value of the horticultural function suddenly decreases while the solution is in view. First-choice trekking enables balanced trekking by randomly creating heirs until something better than the current situation develops. Whenever this is a good strategy there are many (e.g., thousands) heirs in a state. So the first preferred mountain climbing is a special type Random mountain climbing. Description. This is a robust mountaineering algorithm. A person is initiated approximately. ... When the individual reaches a local optimal state a new solution is created approximately and mountaineering begins again. The best first search is a traversal technique, which checks which node is the most reliable and decides which node to visit next by checking it. To this end, it uses the appraisal function to determine travel. Climbing is used to describe traditional 'siege' techniques, where you will climb the mountain several times before being driven to the summit. Albinism, on the other hand, focuses on 'fast and light' climbs. Free climbing was created to describe any style of climbing that is not AIDS related. ... In free climbing, the climber moves the wall under their own force without the use of any special gear (except for the climbing shoes) to help them move upwards. Climbers can only survive for a short time in the 'death zone' at 8000 m and above, where there are numerous challenges. Deep cracks, avalanches, cliffs and snowflakes make the high form of trekking a very dangerous endeavor. Caldwell and George's son use headlamps to illuminate their way, climbing at night when the temperature is cold-meaning their hands sweat less and there is more friction between their rubber shoes and granite. According to the author, climbing mountains is a very difficult task for people and they enjoy crossing obstacles. Mountaineering is neither complete nor optimal, the time complex of O (∞) but the space complex of O (b). There is no special processing data system as mountaineering rejects old nodes.

Recent trends in Management and Commerce, 2021

Mayfly algorithm (MA) is an optimal way to achieve this goal. It is a newly developed algorithm t... more Mayfly algorithm (MA) is an optimal way to achieve this goal. It is a newly developed algorithm that combines the key benefits of PSO, GA and FA, resulting in a hybrid of PSO-GA-FA. Compared with the other seven transformation methods, the performance evaluation performed using the CEC test operations demonstrates the dominance of MA in terms of accumulation rate and velocity. Although this requires rapid integration, it is not yet used in many engineering optimization fields, so we propose to use it for antenna optimization tasks. Predictions for the next century 15 to 95 Cm, the 50 cm 'best estimate' indicates a significant increase in sea level rise over the last century, with records from both the Atlantic and the Pacific in the Northern Hemisphere showing sea increase. However, in most cases, of some sites This condition is reduced due to surface resurfacing or regeneration. Rise is the height of the average level of the ocean surface and the increase in wavelength around it. The mayfly optimization algorithm (MOA) was proposed with a better hybridization of the particle swarm optimization (PSO) and the differential evolution (DE) algorithms. The velocity would be relevant to the Cartesian distance among the relevant individuals.

REST Publisher, 2021

Optional selection technique similar to The Ideal So lution (TOPSIS) is a mu lti-criterion decisi... more Optional selection technique similar to The Ideal So lution (TOPSIS) is a mu lti-criterion decision Is the method of analysis. This was originally Sing-Lai Hwang Created in 1981 by and Yoon, and Yoon and Yoon in 1987. In 1993Further improved by Hwang, Lai and Liu. Became TOPSIS Narrow geometric Distance from selected alternative positive optical solution (PIS) and negative ideal Based on the idea that the solution must have a very long geome tric distance (NIS) Consists of. Identify Weights for each criterion, each Every alternative and best alternative to the criteria Normalizing the marks and geometric distance between Compensation is a method of comparing the set of alternatives by calculation. The assumption of TOPSIS is The criteria increase uniformly or Decrease. Many because of parameters or Criteria scale problems often have Normalizat ion of inappropriate dimensions is common needed. Co mpensation systems such as TOPSIS Trade between criteria A llo w exchanges where bad results on one scale are good results on another scale May be denied by. It offers So much more than unpaid methods Realistic modeling form, in wh ich Alternative solutions are included or excluded In terms of tough cutoffs. Its in nuclear power plants an example of application given.

Data Analytics and Artificial Intelligence, 2021

In evolutionary calculat ion, differential evolution (DE) is a method of developing a problem in ... more In evolutionary calculat ion, differential evolution (DE) is a method of developing a problem in an evolutionary process. Such algorith ms do not make some or all assumptions about the basic optimization problem and can quickly exp lore very large design gaps. Differential Evolut ion (DE) is a co mp lete search algorith m based on population, which is based on a candidate' s evolutionary process. Improves the problem by repeatedly upgrading the solution. Such algorith ms give little or no speculation about the basic optimizat ion problem and will quickly exp lore the larger design gaps; both genetic algorith ms and differential evolution are examp les of evolutionary calculations. Genetic mechanis ms are very clo se to the metaphor of genetic reproduction. ... Different evolution is in the same style, but correspondence is not precise. DE is the processing of the population of individuals represented by the dimensional vectors of real numbers Is an evolutionary mec hanism. In every repetition, in every parent, a mutation is a different mutation driver Created by The mutant then communicates with the parents and gives the offspring a different evolution (DE) a co mpetitive fo rm of evolutionary mechanis ms. It relies heavily on modifying solutions, using measured differences of appro ximately selected indiv iduals fro m the population, to develop new solutions. Differential reproductive success refers to the statistical analysis that compares successful reproduction rat es between groups in a given generation of a speciesin other wo rds, how well each individual group is able to leave offspring, with examples of both genetic mechanisms and different evolution. Evo lutionary calcu lation. Genetic mechanis ms are very close to the metaphor of genetic reproduction. ... Different evolution is in the same style, but correspondence is not precise. DE is the processing of the population of individuals represented by the dimensional vectors of real numbers Is an evolutionary mechanis m. In each iteration, fo r each parent, one with a different mutation driver the mutant is created. The mutant then goes to the parents and gets an offspring

REST Publisher, 2022

Gravitational search algorithm is a naturally occurring algorithm based on Newton's mathematical ... more Gravitational search algorithm is a naturally occurring algorithm based on Newton's mathematical model of the law of gravitation and motion. Over the course of a decade, researchers have provided many variants of the gravitational search algorithm by modifying its parameters to effectively solve complex optimization problems. This paper conducts a comparative analysis of ten types of gravity search algorithms that modify the three parameters of optimum, speed and position. Tests are conducted on two sets of benchmark types, namely standard functions and issues belonging to different types such as CEC2015 functions, univocal, multimodal and unrestricted optimization functions. Performance comparison is evaluated and statistically validated based on the average exercise value and concentration graph. In trials, IGSA has achieved excellent accuracy through a balanced trade between exploration and exploitation. Furthermore, three negative breast cancer datasets were considered to analyze the efficacy of GSA variants for the black section. Different performance analyzes were performed based on both quality and quantity with the integrated jacquard index as a performance measure. Tests confirm that the IGSA based method worked better than other methods.

REST Publisher, 2021

The complex proportional evaluation, COPRAS It is used. for multicriteria evaluation of both. max... more The complex proportional evaluation, COPRAS It is used. for multicriteria evaluation of both. maximizing and minimizing criteria values Complex proportional assessment is an analytical tool for solving multi-criteria decision making problems. ... it seems that the recommended framework of COPRaS-iviF can be satis-factorial implemented in decision making problems under ambiguous and ill-defined conditions. Complex Proportional Assessment (COPRAS) method by 1994 [84-87] by Javatskas, Kokluskas and Sarka Introduced. This method is used to increase and decrease the index values, and the result Increasing and decreasing the index of attributes in the evaluation The effect of is considered separately. For evaluating and ranking hotels Complex Proportional Assessment (COPRAS) model. Compatibility of the proposed structure an empirical example and real-world case study from the Indian tourism industry is provided to check. Finally, the validity of the proposed model Comparison to study character and strength And sensitivity analysis is performed. The diversity of different biases The tendencies of the various dependencies on which they are based are the same Not sampled, these complex algorithms Are identified and reported.