Pub Date : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768518
VishnuPriya Thotakura, Sankararao Majji, S. Karanam, T. V. V. Pavan Kumar, Tulasi Radhika Patnala, H. S
Commercial off-the-shelf semiconductor devices cannot supply system solutions provided by ASIC products. Only a few of the most obvious benefits include lower system costs, smaller volumes and weights, and improved system performance. An ASIC design solution can sometimes be used in conjunction with analogue or mixed-signal designs, but doing so requires weighing various factors, such as the level of available market technology and quality vs. the investment required to set up a mixed-mode design environment and hire sufficient staff. Two mixed-signal devices have been developed using the proposed approaches, and one of those devices (e.g., ABACUS) is part of an ESPRIT project partially funded by the European Commission.
{"title":"Application Specific Digital and Mixed-Signal Integrated Circuit Designs Based on Algorithm Hardware Co-Design","authors":"VishnuPriya Thotakura, Sankararao Majji, S. Karanam, T. V. V. Pavan Kumar, Tulasi Radhika Patnala, H. S","doi":"10.1109/ICEEICT53079.2022.9768518","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768518","url":null,"abstract":"Commercial off-the-shelf semiconductor devices cannot supply system solutions provided by ASIC products. Only a few of the most obvious benefits include lower system costs, smaller volumes and weights, and improved system performance. An ASIC design solution can sometimes be used in conjunction with analogue or mixed-signal designs, but doing so requires weighing various factors, such as the level of available market technology and quality vs. the investment required to set up a mixed-mode design environment and hire sufficient staff. Two mixed-signal devices have been developed using the proposed approaches, and one of those devices (e.g., ABACUS) is part of an ESPRIT project partially funded by the European Commission.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132732076","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768584
Pallav Rawal, Shubhi Jain, Vishal Das, S. Rawat
A frequency reconfigurable antenna for multi-standard wireless communication system is proposed in this letter. The loop antenna with partial ground and a center element with optimized dimension is presented. To obtain the frequency reconfigurability, two PIN diodes are put in the Top plane. The antenna presented is efficient in changing between four different bands of resonant frequency centered at 3.10, 4.17, 4.21, and 17.47 GHz with wide coverage area. CST microwave studio is used to simulate characteristics such as reflection coefficient, VSWR and bandwidth. The suggested antennas can be used in a wide range of wireless communication systems, including Wi-Fi, WLAN, WIMAX, UWB and satellite communication system.
{"title":"A compact slotted rectangular planar antenna with frequency reconfigurability","authors":"Pallav Rawal, Shubhi Jain, Vishal Das, S. Rawat","doi":"10.1109/ICEEICT53079.2022.9768584","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768584","url":null,"abstract":"A frequency reconfigurable antenna for multi-standard wireless communication system is proposed in this letter. The loop antenna with partial ground and a center element with optimized dimension is presented. To obtain the frequency reconfigurability, two PIN diodes are put in the Top plane. The antenna presented is efficient in changing between four different bands of resonant frequency centered at 3.10, 4.17, 4.21, and 17.47 GHz with wide coverage area. CST microwave studio is used to simulate characteristics such as reflection coefficient, VSWR and bandwidth. The suggested antennas can be used in a wide range of wireless communication systems, including Wi-Fi, WLAN, WIMAX, UWB and satellite communication system.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127837661","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768505
C. Karpagam, S. Gomathi alias Rohini
Autism is a behavioural disorder that commonly affects the communication and interaction of an individual. Early detection may deduce symptoms and support the daily living of a person with the assistance of therapy. Many researchers investigate the factors associated with autistic traits that pro-duce meaningful results for further analysis. In this paper, an experiment on one such analysis is focussed on a toddler, child, adolescent and adult autism dataset using a machine learning technique, specifically logistic regression. In the analysis, feature selection techniques applied are chi-square and information gain to reduce the dimensionality of the dataset. The experimental analysis results with a mean accuracy of 90 %. In addition, a few hypotheses are proposed with the evidence obtained from the dataset as an initial step of the research process.
{"title":"An Experiment on Logistic Regression Analysis to Detect Autism Spectrum Disorder","authors":"C. Karpagam, S. Gomathi alias Rohini","doi":"10.1109/ICEEICT53079.2022.9768505","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768505","url":null,"abstract":"Autism is a behavioural disorder that commonly affects the communication and interaction of an individual. Early detection may deduce symptoms and support the daily living of a person with the assistance of therapy. Many researchers investigate the factors associated with autistic traits that pro-duce meaningful results for further analysis. In this paper, an experiment on one such analysis is focussed on a toddler, child, adolescent and adult autism dataset using a machine learning technique, specifically logistic regression. In the analysis, feature selection techniques applied are chi-square and information gain to reduce the dimensionality of the dataset. The experimental analysis results with a mean accuracy of 90 %. In addition, a few hypotheses are proposed with the evidence obtained from the dataset as an initial step of the research process.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127429182","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768442
Akshay Bhosale, Vikram S. Patil, P. Bidkar
Visual Cryptography (VC) can be used for sharing a secret image. The image is distributed among the valid participants in the form of transparencies that are random noise-like images. When the required number of participants superimpose their transparencies, the secret image gets revealed without using any computational power. In this paper, we have proposed an authentication system which uses VC for encrypting the passwords required for downloading and opening the question papers from the server. Two transparencies are created for encrypting two passwords. These transparencies are sent to the internal and external supervisor on their email. To reveal the passwords, both the examiners have to download their transparency and give it as an input to a simple software on a computer, which overlaps them and reveals the passwords. The passwords can also be revealed by physically printing the transparencies and overlapping them. The results are tested using MATLAB.
{"title":"An Authentication System For Online Question Paper Delivery using Visual Cryptography","authors":"Akshay Bhosale, Vikram S. Patil, P. Bidkar","doi":"10.1109/ICEEICT53079.2022.9768442","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768442","url":null,"abstract":"Visual Cryptography (VC) can be used for sharing a secret image. The image is distributed among the valid participants in the form of transparencies that are random noise-like images. When the required number of participants superimpose their transparencies, the secret image gets revealed without using any computational power. In this paper, we have proposed an authentication system which uses VC for encrypting the passwords required for downloading and opening the question papers from the server. Two transparencies are created for encrypting two passwords. These transparencies are sent to the internal and external supervisor on their email. To reveal the passwords, both the examiners have to download their transparency and give it as an input to a simple software on a computer, which overlaps them and reveals the passwords. The passwords can also be revealed by physically printing the transparencies and overlapping them. The results are tested using MATLAB.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115532076","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768578
Anjana Yadav, Balveer Singh
The data cube assessments dependent on Online Analytical Processing (OLAP) trouble for numerous depositing splendors over broad information. In favor of appreciating question answering era pleasant with OLAP skeleton patrons and allowing complete industry organized notice compulsory, OLAP information is organized as a data cube model. The OLAP questions are answered in rapid and sturdy time by exploiting the cube embodiment for appraisals buyers. Until now this moreover insets insupportable charge, concerning to accumulation remembrance and time, yet as a data storage area had a typical length and extent which will be influential on stimulating procedure. Thus, cube classification has visited to be refined fascinating to moderate question managing charge, preserving as a control the materializing breach. Numerous strategies and heuristics like divergence and voracious approaches have been exploited to suggest a vague solution. Here, a Grey Wolf Optimization (GWO) strategy is exploited in a lattice structure for finding the best data cube to decrease the question processing charge. The outputs describe the superior efficiency of GWO against GA, PSO and ALO based on total dimensions and frequency.
{"title":"A Grey Wolf Optimization (GWO) based Cube Selection in OLAP Data Model","authors":"Anjana Yadav, Balveer Singh","doi":"10.1109/ICEEICT53079.2022.9768578","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768578","url":null,"abstract":"The data cube assessments dependent on Online Analytical Processing (OLAP) trouble for numerous depositing splendors over broad information. In favor of appreciating question answering era pleasant with OLAP skeleton patrons and allowing complete industry organized notice compulsory, OLAP information is organized as a data cube model. The OLAP questions are answered in rapid and sturdy time by exploiting the cube embodiment for appraisals buyers. Until now this moreover insets insupportable charge, concerning to accumulation remembrance and time, yet as a data storage area had a typical length and extent which will be influential on stimulating procedure. Thus, cube classification has visited to be refined fascinating to moderate question managing charge, preserving as a control the materializing breach. Numerous strategies and heuristics like divergence and voracious approaches have been exploited to suggest a vague solution. Here, a Grey Wolf Optimization (GWO) strategy is exploited in a lattice structure for finding the best data cube to decrease the question processing charge. The outputs describe the superior efficiency of GWO against GA, PSO and ALO based on total dimensions and frequency.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124179450","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768598
K. L. Lasya, D. Lahari, R. Akarsha, A. Lavanya, K. Prakash, Duc-Tan Tran
The devastating spread caused by Severe Acute Respiratory Disorder - Coronavirus (SARS-CoV-2) which is also known as COVID-2019 has brought global threat to our society. Every country is making immense efforts to stop the spread of the deadly disease through the use of finance, infrastructure and data sources, as well as protective devices, life-risk treatments, as well as other sources. Researchers studying artificial intelligence focus their skills to create mathematical models for studying the scourge of this disease using and shared data. In order to improve the wellbeing of our society. This article proposes using model of deep and machine-learning to understand its daily exponential behavior, as well as the prediction of the future impact of the COVID-2019 across nations using the live data of the Johns Hopkins dashboard
{"title":"Analysis and Prediction of COVID-19 datasets using Machine Learning Algorithms","authors":"K. L. Lasya, D. Lahari, R. Akarsha, A. Lavanya, K. Prakash, Duc-Tan Tran","doi":"10.1109/ICEEICT53079.2022.9768598","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768598","url":null,"abstract":"The devastating spread caused by Severe Acute Respiratory Disorder - Coronavirus (SARS-CoV-2) which is also known as COVID-2019 has brought global threat to our society. Every country is making immense efforts to stop the spread of the deadly disease through the use of finance, infrastructure and data sources, as well as protective devices, life-risk treatments, as well as other sources. Researchers studying artificial intelligence focus their skills to create mathematical models for studying the scourge of this disease using and shared data. In order to improve the wellbeing of our society. This article proposes using model of deep and machine-learning to understand its daily exponential behavior, as well as the prediction of the future impact of the COVID-2019 across nations using the live data of the Johns Hopkins dashboard","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114600571","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}
Breast cancer is the most frequent malignancy discovered in women across the world. The early and accurate diagnosis of breast cancer is critical for lowering the mortality rate and raising the odds of successful therapy. The goal of this paper is to provide a technique for conducting early breast cancer diagnosis via machine learning and IoT. The main aim of the paper is to provide an alternative to the conventional diagnosis technique by using several machine learning algorithms. Breast cancer diagnosis using machine learning is a non-invasive technique with high accuracy rate. The proposed technique showed accuracy of 92.98 percent, 96.49 percent,97.36 percent, and 98.24 percent using the decision tree, random forest, logistic regression, and eXtreme gradient boosting algorithms, respectively. It was evident through the obtained results that the eXtreme gradient boosting yields the highest accuracy.
{"title":"Framework for Breast Cancer Diagnosis Using Machine Learning and IoT","authors":"Chandrashish Roy, Ishanee Mazumder, Subhra Debdas, Subhankar Samanta, Subhrajit Singha Roy","doi":"10.1109/ICEEICT53079.2022.9768469","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768469","url":null,"abstract":"Breast cancer is the most frequent malignancy discovered in women across the world. The early and accurate diagnosis of breast cancer is critical for lowering the mortality rate and raising the odds of successful therapy. The goal of this paper is to provide a technique for conducting early breast cancer diagnosis via machine learning and IoT. The main aim of the paper is to provide an alternative to the conventional diagnosis technique by using several machine learning algorithms. Breast cancer diagnosis using machine learning is a non-invasive technique with high accuracy rate. The proposed technique showed accuracy of 92.98 percent, 96.49 percent,97.36 percent, and 98.24 percent using the decision tree, random forest, logistic regression, and eXtreme gradient boosting algorithms, respectively. It was evident through the obtained results that the eXtreme gradient boosting yields the highest accuracy.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124012433","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768536
M. Abhilash, E. B. Benoygopal, Prakash Rosayyan, Hemant Jeevan Magadum, G. Satheesh
Traffic congestion is becoming a huge problem for many major cities. Additional infrastructure such as roads and flyovers shall be constructed to avoid traffic congestion. But additional infrastructure is an expensive choice and not a permanent solution. A holistic and intelligent solution should be developed to tackle the city traffic problems. If public transportation systems like buses are more comfortable and faster means of transport then people shall eventually switch their mode of travel and start using buses instead of private vehicles. This will reduce the number of vehicles on the road thus reducing congestion. Technologies like Bus Rapid Transit (BRT) greatly help in giving priority to public buses and promoting public transportation. However, the BRT system uses dedicated lanes to reduce travel time. In this paper, we propose a Bus Priority System for Heterogeneous traffic conditions (BPSH) without having a dedicated lane for buses. The proposed technique was experimented at Indore Madyapradesh India and the results show that the average travel time and delay of BRT buses drastically reduced to 70% after implementing the BPSH system.
{"title":"Bus Priority System for Heterogeneous Traffic Conditions","authors":"M. Abhilash, E. B. Benoygopal, Prakash Rosayyan, Hemant Jeevan Magadum, G. Satheesh","doi":"10.1109/ICEEICT53079.2022.9768536","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768536","url":null,"abstract":"Traffic congestion is becoming a huge problem for many major cities. Additional infrastructure such as roads and flyovers shall be constructed to avoid traffic congestion. But additional infrastructure is an expensive choice and not a permanent solution. A holistic and intelligent solution should be developed to tackle the city traffic problems. If public transportation systems like buses are more comfortable and faster means of transport then people shall eventually switch their mode of travel and start using buses instead of private vehicles. This will reduce the number of vehicles on the road thus reducing congestion. Technologies like Bus Rapid Transit (BRT) greatly help in giving priority to public buses and promoting public transportation. However, the BRT system uses dedicated lanes to reduce travel time. In this paper, we propose a Bus Priority System for Heterogeneous traffic conditions (BPSH) without having a dedicated lane for buses. The proposed technique was experimented at Indore Madyapradesh India and the results show that the average travel time and delay of BRT buses drastically reduced to 70% after implementing the BPSH system.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125757433","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768577
M. Magesh, P. K. Jawahar, S. Saranya
The proposed work deals with the study of automatic tuning of PID controllers for perched landing of UAV'S with shape memory This modeling considerably enhanced the range of feasible structures for perch and rest compared with avian-inspired influencers. Though not nature-inspired, and far easier than a foot from a bird, stiff fingers and contact modules were easier to create than avian-inspired gripers with several joint joints per finger and stronger and more durable. Start and landing in flight phases are critical phases.polymer based auxetic landing gears. A metaheuristic tuning is implemented through spider monkey approach for PID controllers in drone perching mechanism. Trials were conducted with open loop for drone perching conditions in measuring the error rates pitch, yaw and roll moment. Fitness function is calculated through regression analysis for the observed experiments. Spider monkey based optimization algorithm is implemented for the fitness function to find the optimal data of Kp, Ki and Kd for minimal error rate of pitch, yaw and roll moment to balance the drone at various perching angles. The provided results have been compared with model predictive controller (MPC) and Generic model control (GMC). It has been noted that SM based PID controller reduces the maximum error rates with 34.6% when compared with MPC and 24.8% when compared with GMC.
{"title":"Spider monkey based metaheuristic tuning of PID controllers for stability landing of UAV'S with SMP-Auxetic landing gears","authors":"M. Magesh, P. K. Jawahar, S. Saranya","doi":"10.1109/ICEEICT53079.2022.9768577","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768577","url":null,"abstract":"The proposed work deals with the study of automatic tuning of PID controllers for perched landing of UAV'S with shape memory This modeling considerably enhanced the range of feasible structures for perch and rest compared with avian-inspired influencers. Though not nature-inspired, and far easier than a foot from a bird, stiff fingers and contact modules were easier to create than avian-inspired gripers with several joint joints per finger and stronger and more durable. Start and landing in flight phases are critical phases.polymer based auxetic landing gears. A metaheuristic tuning is implemented through spider monkey approach for PID controllers in drone perching mechanism. Trials were conducted with open loop for drone perching conditions in measuring the error rates pitch, yaw and roll moment. Fitness function is calculated through regression analysis for the observed experiments. Spider monkey based optimization algorithm is implemented for the fitness function to find the optimal data of Kp, Ki and Kd for minimal error rate of pitch, yaw and roll moment to balance the drone at various perching angles. The provided results have been compared with model predictive controller (MPC) and Generic model control (GMC). It has been noted that SM based PID controller reduces the maximum error rates with 34.6% when compared with MPC and 24.8% when compared with GMC.","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125797857","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 : 2022-02-16DOI: 10.1109/ICEEICT53079.2022.9768646
V. Shobana, K. Nandhini
Ensemble plays a major role in machine learning algorithms, and it can improve the performance of the single model by combining two or more models. It can be able to combine a number of different models and comes out with a promising result. There are several ensemble techniques such as bagging, boosting, and stacking each of which performs in its own way and produces the results. In this work the different techniques of ensembling are being explored and has been tested its working on the sample dataset. The results are varying in performance and suits well for the taken data points. Keywords: ensemble, stacking, boosting, bagging, ensemble learners
{"title":"Ensemble Techniques to improve the performance of the High Dimensional MultiClass Algorithms","authors":"V. Shobana, K. Nandhini","doi":"10.1109/ICEEICT53079.2022.9768646","DOIUrl":"https://doi.org/10.1109/ICEEICT53079.2022.9768646","url":null,"abstract":"Ensemble plays a major role in machine learning algorithms, and it can improve the performance of the single model by combining two or more models. It can be able to combine a number of different models and comes out with a promising result. There are several ensemble techniques such as bagging, boosting, and stacking each of which performs in its own way and produces the results. In this work the different techniques of ensembling are being explored and has been tested its working on the sample dataset. The results are varying in performance and suits well for the taken data points. Keywords: ensemble, stacking, boosting, bagging, ensemble learners","PeriodicalId":201910,"journal":{"name":"2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129868851","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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