Pub Date : 2018-02-01DOI: 10.1109/RAETCS.2018.8443785
A. Mabu, R. Prasad, Raghav Yadav, S. Jauro
Bioinformatics refers to the collection, classification, storage and the scrutiny of biochemical and biological data. It utilizes personal computers especially, as implemented toward molecular genetics and genomics. It is a quickly emerging division of science and is exceedingly interdisciplinary, utilizing strategies and ideas from basic science and linguistics. This paper, initially display a review of the current and next generation sequencing (NGS) technologies and pointed out some problems regarding its data analysis capability. We present the current bioinformatics methods and proficiency of the prediction based data mining algorithms. The fundamental rule that support bioinformatics analysis has been conferred. Based on the estimation of the chief analysis instruments, we have displayed the overview of various data mining algorithms for the assortment of various examination tools applicable in particular research errands. We also analyze the difficulties in extensive scale data mining, furthermore, administration in the arena of bioinformatics and assessed numerous algorithms' performance grounded on watching error rate they yield in different papers.
{"title":"A Review of Data Mining Methods in Bioinformatics","authors":"A. Mabu, R. Prasad, Raghav Yadav, S. Jauro","doi":"10.1109/RAETCS.2018.8443785","DOIUrl":"https://doi.org/10.1109/RAETCS.2018.8443785","url":null,"abstract":"Bioinformatics refers to the collection, classification, storage and the scrutiny of biochemical and biological data. It utilizes personal computers especially, as implemented toward molecular genetics and genomics. It is a quickly emerging division of science and is exceedingly interdisciplinary, utilizing strategies and ideas from basic science and linguistics. This paper, initially display a review of the current and next generation sequencing (NGS) technologies and pointed out some problems regarding its data analysis capability. We present the current bioinformatics methods and proficiency of the prediction based data mining algorithms. The fundamental rule that support bioinformatics analysis has been conferred. Based on the estimation of the chief analysis instruments, we have displayed the overview of various data mining algorithms for the assortment of various examination tools applicable in particular research errands. We also analyze the difficulties in extensive scale data mining, furthermore, administration in the arena of bioinformatics and assessed numerous algorithms' performance grounded on watching error rate they yield in different papers.","PeriodicalId":131311,"journal":{"name":"2018 Recent Advances on Engineering, Technology and Computational Sciences (RAETCS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125195291","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 : 2018-02-01DOI: 10.1109/RAETCS.2018.8443847
D. Lal, Ajit Kumar Barisal, M. Tripathy
This article presents load frequency control of multi area interconnected microgrid power system. A Fuzzy proportional-integral-derivative (Fuzzy PID) controller is proposed as frequency controller for the system. The present work involves bio-inspired grasshopper optimization algorithm (GOA) for tuning of controller gains. The attainment of proposed Fuzzy PID controller is accounted with that of proportional- integral–derivative (PID) controller. The comparison of system performance is also carried out with and without energy storage system in microgrids. The system performance is also studied with system parameters change and random step load perturbations (SLPs).
{"title":"Load Frequency Control of Multi Area Interconnected Microgrid Power System using Grasshopper Optimization Algorithm Optimized Fuzzy PID Controller","authors":"D. Lal, Ajit Kumar Barisal, M. Tripathy","doi":"10.1109/RAETCS.2018.8443847","DOIUrl":"https://doi.org/10.1109/RAETCS.2018.8443847","url":null,"abstract":"This article presents load frequency control of multi area interconnected microgrid power system. A Fuzzy proportional-integral-derivative (Fuzzy PID) controller is proposed as frequency controller for the system. The present work involves bio-inspired grasshopper optimization algorithm (GOA) for tuning of controller gains. The attainment of proposed Fuzzy PID controller is accounted with that of proportional- integral–derivative (PID) controller. The comparison of system performance is also carried out with and without energy storage system in microgrids. The system performance is also studied with system parameters change and random step load perturbations (SLPs).","PeriodicalId":131311,"journal":{"name":"2018 Recent Advances on Engineering, Technology and Computational Sciences (RAETCS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115444603","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 : 2018-02-01DOI: 10.1109/RAETCS.2018.8443866
Ayman Almabruk Mahmud, W. Jeberson
This paper discourses the real time issues of aircraft scheduling. The concern of finding an ideal schedule aimed at aircraft landings is mentioned as the “aircraft landing problem” As every aircraft has a favored landing time, the aim is to diminish the aggregate delay costs meant for the whole aircraft landings while regarding the separation requirements. The chief goal is to diminish the overall cost along with improving aircraft scheduling performance. The proposed work has the subsequent stages, initially the aircrafts are divided as separate classes i.e., heavy, large along with small classes. For each and every aircraft classes, runway occupation profile, landing time and separation times are measured. Entropy value is calculated for the measured parameters. These entropy values are optimized by utilizing Cuckoo-search optimization algorithm. The optimized values are finally scheduled using FCFS algorithm. The employment of entropy based optimization and scheduling offers enhanced performance when paralleled with the prevailing efforts. The performance of proposed and existing results are contrasted and plotted.
{"title":"Optimized Entropy Based Algorithm for Aircraft Scheduling Problem","authors":"Ayman Almabruk Mahmud, W. Jeberson","doi":"10.1109/RAETCS.2018.8443866","DOIUrl":"https://doi.org/10.1109/RAETCS.2018.8443866","url":null,"abstract":"This paper discourses the real time issues of aircraft scheduling. The concern of finding an ideal schedule aimed at aircraft landings is mentioned as the “aircraft landing problem” As every aircraft has a favored landing time, the aim is to diminish the aggregate delay costs meant for the whole aircraft landings while regarding the separation requirements. The chief goal is to diminish the overall cost along with improving aircraft scheduling performance. The proposed work has the subsequent stages, initially the aircrafts are divided as separate classes i.e., heavy, large along with small classes. For each and every aircraft classes, runway occupation profile, landing time and separation times are measured. Entropy value is calculated for the measured parameters. These entropy values are optimized by utilizing Cuckoo-search optimization algorithm. The optimized values are finally scheduled using FCFS algorithm. The employment of entropy based optimization and scheduling offers enhanced performance when paralleled with the prevailing efforts. The performance of proposed and existing results are contrasted and plotted.","PeriodicalId":131311,"journal":{"name":"2018 Recent Advances on Engineering, Technology and Computational Sciences (RAETCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129849175","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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