Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9752899
J. Ramkumar, C. Kumuthini, B. Narasimhan, S. Boopalan
Ad-hoc networks with poor routing affects the complete network and it leads to enhanced delay in delivering the packets to destination and consumption of energy in an exhaustive manner. Significant task of CR-MANET is to find a better route which consumes less delay and energy. This paper proposes an enriched version of ad-hoc on-demand distance vector (EAODV) routing protocol to meet the challenges faced in CR-MANET. EAODV involves four different phases which are route request method, updating the routing table, route request on demand and route lifetime. These four phases help EAODV to avoid congestion and discover better route to destination. EAODV is intended to locate the best alternative route in a short period of time amid route failure by dynamically selecting the optimal route. Before sending the packets, EAODV evaluates the selected routes using the residual energy of nodes in the path. If it is not satisfied, then next best route is selected. Efficiency of EAODV is demonstrated by a comprehensive simulation and it got resulted in better outcomes in terms of minimizing delay and energy consumption.
{"title":"Energy Consumption Minimization in Cognitive Radio Mobile Ad-Hoc Networks using Enriched Ad-hoc On-demand Distance Vector Protocol","authors":"J. Ramkumar, C. Kumuthini, B. Narasimhan, S. Boopalan","doi":"10.1109/ICACTA54488.2022.9752899","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9752899","url":null,"abstract":"Ad-hoc networks with poor routing affects the complete network and it leads to enhanced delay in delivering the packets to destination and consumption of energy in an exhaustive manner. Significant task of CR-MANET is to find a better route which consumes less delay and energy. This paper proposes an enriched version of ad-hoc on-demand distance vector (EAODV) routing protocol to meet the challenges faced in CR-MANET. EAODV involves four different phases which are route request method, updating the routing table, route request on demand and route lifetime. These four phases help EAODV to avoid congestion and discover better route to destination. EAODV is intended to locate the best alternative route in a short period of time amid route failure by dynamically selecting the optimal route. Before sending the packets, EAODV evaluates the selected routes using the residual energy of nodes in the path. If it is not satisfied, then next best route is selected. Efficiency of EAODV is demonstrated by a comprehensive simulation and it got resulted in better outcomes in terms of minimizing delay and energy consumption.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122500689","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753597
Ishani Mishra, S. L., Umadevi, D. M, N. Prasanna, Manisha Prem
Semantic Segmentation is extensively utilized in fields like Medical, Surgery planning, Seismic imaging, Machine vision, etc. It divides each pixel of unique image into separate classes. Marine predator's algorithm is the meta heuristic algorithm which excited us to utilize for semantic segmentation with regard to products of agriculture. This paper compares wide variety of algorithms along with advantages and disadvantages for semantic segmentation and This algorithm has been selected for procedure of semantic segmentation as to differentiate a crop and weed successfully.
{"title":"Enhanced Framework for Semantic Segmentation of Agricultural Products","authors":"Ishani Mishra, S. L., Umadevi, D. M, N. Prasanna, Manisha Prem","doi":"10.1109/ICACTA54488.2022.9753597","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753597","url":null,"abstract":"Semantic Segmentation is extensively utilized in fields like Medical, Surgery planning, Seismic imaging, Machine vision, etc. It divides each pixel of unique image into separate classes. Marine predator's algorithm is the meta heuristic algorithm which excited us to utilize for semantic segmentation with regard to products of agriculture. This paper compares wide variety of algorithms along with advantages and disadvantages for semantic segmentation and This algorithm has been selected for procedure of semantic segmentation as to differentiate a crop and weed successfully.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131034362","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753341
M. Sujaritha, M. Kavitha, S. Shunmugapriya, R. S. Vikram, C. Somasundaram, R. Yogeshwaran
This paper is mainly intended to use Bat Algorithm (BA) – based clustering approach for classifying multispectral satellite images. This clustering algorithm provides the partitions that are both bound and self-determined. But the drawbacks of traditional K-means algorithm are: i) it converges easily to a local optimum and ii) identifying the number of optimal clusters is a challenging task. The researchers have tried to unravel these issues by initializing the cluster centers from a priori information. In this paper, we have tried to solve the issues of traditional k-means algorithm by applying the bat algorithm on it. The proposed modified bat algorithm is used to segment the satellite images and extract the useful information from it. In the proposed algorithm, clusters with minimum inter-cluster distance and lesser than the given threshold are identified and merged. This process is repeated till all the inter-cluster distances are greater than the given threshold. The enhancement in the performance of the proposed improved bat algorithm is evident in the experimental results.
{"title":"Multispectral Satellite Image Segmentation Using Improved Bat Algorithm","authors":"M. Sujaritha, M. Kavitha, S. Shunmugapriya, R. S. Vikram, C. Somasundaram, R. Yogeshwaran","doi":"10.1109/ICACTA54488.2022.9753341","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753341","url":null,"abstract":"This paper is mainly intended to use Bat Algorithm (BA) – based clustering approach for classifying multispectral satellite images. This clustering algorithm provides the partitions that are both bound and self-determined. But the drawbacks of traditional K-means algorithm are: i) it converges easily to a local optimum and ii) identifying the number of optimal clusters is a challenging task. The researchers have tried to unravel these issues by initializing the cluster centers from a priori information. In this paper, we have tried to solve the issues of traditional k-means algorithm by applying the bat algorithm on it. The proposed modified bat algorithm is used to segment the satellite images and extract the useful information from it. In the proposed algorithm, clusters with minimum inter-cluster distance and lesser than the given threshold are identified and merged. This process is repeated till all the inter-cluster distances are greater than the given threshold. The enhancement in the performance of the proposed improved bat algorithm is evident in the experimental results.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131127266","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9752893
C. Gobinath, M. P. Gopinath
In ophthalmology, fundus image analysis is an efficient way to avoid blindness. Existing deep learning methods with fundus images fail to attain high classification performance because there are considerable numbers of pixel wise annotated data are used for training. The proposed work examines the performance of semi-supervised generative adversarial network from labeled ODIR dataset and from private dataset available in hospital. Training process is enhanced by using unlabeled dataset at various levels, weights which are updated frequently in training phase and finally test phase with labeled ODIR dataset improves classification accuracy. The optimized loss function is used to update weight parameters of discriminator and generator. The wide-ranging research shows that our model achieves state-of-art retinal classification accuracy by using ODIR and hospital dataset.
{"title":"Deep Classification of Fundus Images Using Semi Supervised GAN","authors":"C. Gobinath, M. P. Gopinath","doi":"10.1109/ICACTA54488.2022.9752893","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9752893","url":null,"abstract":"In ophthalmology, fundus image analysis is an efficient way to avoid blindness. Existing deep learning methods with fundus images fail to attain high classification performance because there are considerable numbers of pixel wise annotated data are used for training. The proposed work examines the performance of semi-supervised generative adversarial network from labeled ODIR dataset and from private dataset available in hospital. Training process is enhanced by using unlabeled dataset at various levels, weights which are updated frequently in training phase and finally test phase with labeled ODIR dataset improves classification accuracy. The optimized loss function is used to update weight parameters of discriminator and generator. The wide-ranging research shows that our model achieves state-of-art retinal classification accuracy by using ODIR and hospital dataset.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132841394","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753270
R. Paulraj, S. B. V., G. V. Vardhan, K. S. Pradeep, K. Hemanth, G. B. Reddy
Our lives has become simpler with Quick gradual addition of innovation and framework. Approach of innovation has additionally risen traffic dangers and street Mishap occur over and over which causes gigantic death toll and property due to the helpless crisis offices. As of late, astute transportation frameworks ITS have arisen as a productive method of further developing understanding of transportation frameworks and improving travel wellbeing. Mishap location frameworks are one of the best ITS apparatuses. The Mishap distinguished framework is based on Global Positioning System GPS and Global System for Mobile correspondence GSM can be achieved with one or few sensors, the framework can accumulate data and directions of Mishap spot then, at that point, send this information to salvages administrations focus over an organization interface in most brief time, it addressed as an occurrence making a difference framework. In this paper, we have proposed a clever framework that made out of a GPS collector, Vibration sensor, GSM Modem and incorporated with Vehicular AD-Hoc Network VANET. The utilization of VANET by improved Ad hoc On-Demand Distance Vector convention AODV helps these administrations in tracking down the ideal course to the crisis message. The utilization of GSM, GPS, and VANET innovations permits the framework to follow vehicle and gives the most moment.
{"title":"A Detailed Approach on Vehicle Accident Recognition and Remote Alarm Device","authors":"R. Paulraj, S. B. V., G. V. Vardhan, K. S. Pradeep, K. Hemanth, G. B. Reddy","doi":"10.1109/ICACTA54488.2022.9753270","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753270","url":null,"abstract":"Our lives has become simpler with Quick gradual addition of innovation and framework. Approach of innovation has additionally risen traffic dangers and street Mishap occur over and over which causes gigantic death toll and property due to the helpless crisis offices. As of late, astute transportation frameworks ITS have arisen as a productive method of further developing understanding of transportation frameworks and improving travel wellbeing. Mishap location frameworks are one of the best ITS apparatuses. The Mishap distinguished framework is based on Global Positioning System GPS and Global System for Mobile correspondence GSM can be achieved with one or few sensors, the framework can accumulate data and directions of Mishap spot then, at that point, send this information to salvages administrations focus over an organization interface in most brief time, it addressed as an occurrence making a difference framework. In this paper, we have proposed a clever framework that made out of a GPS collector, Vibration sensor, GSM Modem and incorporated with Vehicular AD-Hoc Network VANET. The utilization of VANET by improved Ad hoc On-Demand Distance Vector convention AODV helps these administrations in tracking down the ideal course to the crisis message. The utilization of GSM, GPS, and VANET innovations permits the framework to follow vehicle and gives the most moment.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115546751","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753553
V. Ramya, N. Kousika, P. Rajasekaran, Vijeyakaveri. V, J. Jaganpradeep
Mobile Ad-hoc Network (MANET) can be a self configured commercial road and rail network with less community of cordless contact. A several routing standard protocol is being advanced for MANET routing plus provide safety measures mechanism to stop security posts. Dynamic Partition Routing (DPR), one of the popular reactive routing practices for MANET, establishes way between origin to hot spot before files communication come about using Route request (RREQ) and Route reply (RREP) control announcements. The Modified Dynamic Partition Routing in (MDPR) intended for prevent option diversion because of a malicious computer in the market using group Diffie-Hellman (GDH) key, about any intermediate dependable node commence to misbehave subsequently there is no reduction mechanism. The employed Hash scheme can identify the misbehaving beginner's node which could provide inappropriate target. Our planned system testifies the reliability of the desired location and also protect against from acting up intermediary states.
{"title":"Secure and Efficient Modified Dynamic Partition Routing Algorithm for Mobile Ad Hoc Networks","authors":"V. Ramya, N. Kousika, P. Rajasekaran, Vijeyakaveri. V, J. Jaganpradeep","doi":"10.1109/ICACTA54488.2022.9753553","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753553","url":null,"abstract":"Mobile Ad-hoc Network (MANET) can be a self configured commercial road and rail network with less community of cordless contact. A several routing standard protocol is being advanced for MANET routing plus provide safety measures mechanism to stop security posts. Dynamic Partition Routing (DPR), one of the popular reactive routing practices for MANET, establishes way between origin to hot spot before files communication come about using Route request (RREQ) and Route reply (RREP) control announcements. The Modified Dynamic Partition Routing in (MDPR) intended for prevent option diversion because of a malicious computer in the market using group Diffie-Hellman (GDH) key, about any intermediate dependable node commence to misbehave subsequently there is no reduction mechanism. The employed Hash scheme can identify the misbehaving beginner's node which could provide inappropriate target. Our planned system testifies the reliability of the desired location and also protect against from acting up intermediary states.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115926681","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9752978
K. P., Theophila Vaiz R, P. S, Roshan Ram R
The idea of this paper is to propose a solution to the challenges that students and instructors in the institution are experiencing as a result of this epidemic. Discovering and manipulating new ideas and concepts of online education is evolving at a rapid pace as the world develops with new technologies. To establish a vibrant, educational and supportive alumni network Student companion is developed. Student companion is an online classroom tool where students may communicate with one another, see presentations and engage with the resources in the tool. The student companion tool makes it simple for students and instructors to connect both within and outside the classroom. Student companion helps to establish courses, distribute assignments, interact and remain organized while saving paper and time. Student companion tool ensures that alumni are treated as important stakeholders by involving them in activities such as video conferencing to clear doubts, various study materials based on industrial needs, seminars, webinars for placements, higher education, mentorship for their projects and hackathons. The desired learning and mentorship take place not just in the classroom, but also outside of it, because students can access Student companion tool online from anywhere and at any time.
{"title":"A Standalone Application for Effective Education","authors":"K. P., Theophila Vaiz R, P. S, Roshan Ram R","doi":"10.1109/ICACTA54488.2022.9752978","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9752978","url":null,"abstract":"The idea of this paper is to propose a solution to the challenges that students and instructors in the institution are experiencing as a result of this epidemic. Discovering and manipulating new ideas and concepts of online education is evolving at a rapid pace as the world develops with new technologies. To establish a vibrant, educational and supportive alumni network Student companion is developed. Student companion is an online classroom tool where students may communicate with one another, see presentations and engage with the resources in the tool. The student companion tool makes it simple for students and instructors to connect both within and outside the classroom. Student companion helps to establish courses, distribute assignments, interact and remain organized while saving paper and time. Student companion tool ensures that alumni are treated as important stakeholders by involving them in activities such as video conferencing to clear doubts, various study materials based on industrial needs, seminars, webinars for placements, higher education, mentorship for their projects and hackathons. The desired learning and mentorship take place not just in the classroom, but also outside of it, because students can access Student companion tool online from anywhere and at any time.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"148 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120871404","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753357
M. Hannula
In this study a challenging binary classification was done with a large (>100GB, hundreds of subjects in total) annotated MRI-dataset in public a competition between over thousand teams with their proposals for the problem. For the classification an advanced deep neural network consisting of tailored structural elements having capabilities for detecting small abstract level features from the image data was developed and tested. The resulted ROC was 0,74 in the test data ($mathrm{N}=87$) and 0,55 in the extended test data phase; the results were among other proposals (>1000 solutions) in the top 5-25%, correspondingly. The relevance and accuracy of the solution was discussed including a specific finding about interesting differences in the classification performance between the data from different types of MRI-scans, being in line with other independent research findings. This may indicate the results of the deep neural network provide some additional value about the presence of MGMT. However, in general level the topic is still open and requires further studies to achieve a better understanding.
{"title":"About the Accuracy and Relevance of Deep Learning in a Challenging MRI-Image Classification Problem","authors":"M. Hannula","doi":"10.1109/ICACTA54488.2022.9753357","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753357","url":null,"abstract":"In this study a challenging binary classification was done with a large (>100GB, hundreds of subjects in total) annotated MRI-dataset in public a competition between over thousand teams with their proposals for the problem. For the classification an advanced deep neural network consisting of tailored structural elements having capabilities for detecting small abstract level features from the image data was developed and tested. The resulted ROC was 0,74 in the test data ($mathrm{N}=87$) and 0,55 in the extended test data phase; the results were among other proposals (>1000 solutions) in the top 5-25%, correspondingly. The relevance and accuracy of the solution was discussed including a specific finding about interesting differences in the classification performance between the data from different types of MRI-scans, being in line with other independent research findings. This may indicate the results of the deep neural network provide some additional value about the presence of MGMT. However, in general level the topic is still open and requires further studies to achieve a better understanding.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128371827","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753195
Babu M, R. R., N. V, Mohanambikai A, Monikadevi A, L. S
Nearly 60% highway smash-ups can elude if the driver of the motor vehicle was provided caution not less than one-half second earlier to a collision. Inter-vehicle communication technology has been enabled to upgrade the security of the passengers in the vehicle to overcome problems. Using this technology, the vehicle operators can send and receive safety alter-sounds or messages. These messages are transmitted using Li-Fi technology, and those messages are displayed on the LCD. We use an LED panel to send the data and a photodetector at the receiving end to receive the data. SMS4-BSK algorithm is implemented to provide secure communication between the vehicles.
{"title":"Inter-Vehicle Communication with Improved Security","authors":"Babu M, R. R., N. V, Mohanambikai A, Monikadevi A, L. S","doi":"10.1109/ICACTA54488.2022.9753195","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753195","url":null,"abstract":"Nearly 60% highway smash-ups can elude if the driver of the motor vehicle was provided caution not less than one-half second earlier to a collision. Inter-vehicle communication technology has been enabled to upgrade the security of the passengers in the vehicle to overcome problems. Using this technology, the vehicle operators can send and receive safety alter-sounds or messages. These messages are transmitted using Li-Fi technology, and those messages are displayed on the LCD. We use an LED panel to send the data and a photodetector at the receiving end to receive the data. SMS4-BSK algorithm is implemented to provide secure communication between the vehicles.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128491317","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}
Pub Date : 2022-03-04DOI: 10.1109/ICACTA54488.2022.9753618
C. Bagavathi, S. Padmapriya, H. Mangalam
Evolutionary Algorithms (EA) are standard search mechanisms that use Natural Selection and Survival of the Best as the fundamental algorithm progressing mechanism. The parameterless portfolio is a special technique designed to resolve various categories of problems without any prior requirement of parameter setting. This technique involves an increase in computational effort that can be considered acceptable. In this work, parameterless swarm algorithm using the method of Particle Swarm Optimization has been defined for the application of Traveling Salesman Problem. The performance of the algorithm through the application of parameterless portfolio has been analysed and it can be deduced that the effort of making the Evolutionary Process parameterless can be justified through the benefits discussed in this work.
{"title":"Analysis of Parameterless Particle Swarm Algorithm for Traveling Salesman Problem","authors":"C. Bagavathi, S. Padmapriya, H. Mangalam","doi":"10.1109/ICACTA54488.2022.9753618","DOIUrl":"https://doi.org/10.1109/ICACTA54488.2022.9753618","url":null,"abstract":"Evolutionary Algorithms (EA) are standard search mechanisms that use Natural Selection and Survival of the Best as the fundamental algorithm progressing mechanism. The parameterless portfolio is a special technique designed to resolve various categories of problems without any prior requirement of parameter setting. This technique involves an increase in computational effort that can be considered acceptable. In this work, parameterless swarm algorithm using the method of Particle Swarm Optimization has been defined for the application of Traveling Salesman Problem. The performance of the algorithm through the application of parameterless portfolio has been analysed and it can be deduced that the effort of making the Evolutionary Process parameterless can be justified through the benefits discussed in this work.","PeriodicalId":345370,"journal":{"name":"2022 International Conference on Advanced Computing Technologies and Applications (ICACTA)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122543991","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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