Pub Date : 2020-04-01DOI: 10.4018/ijssci.2020040103
Roseclaremath A. Caroro, Rolysent K. Paredes, Jerry M. Lumasag
Syllabication is essential in the preprocessing stage of speech systems. In the context of the Philippines' Cebuano-Visayan language's syllabication rules, the existing rules do not include hyphenated words although the hyphen defines the syllable boundary in a word. Hence, this study created grammar rules for hyphenated words which include sequences of a hyphen between vowel-consonant, consonant-consonant, vowel-vowel, and consonant-vowel. The test was done for the enhanced grammar rules for Cebuano-Visayan syllabication with 1,465 representative hyphenated and non-hyphenated words of varying lengths. The result further implies that the syllabication analysis for hyphenated words showed that hyphens improve the naturalness and intelligibility in the utterance of the words, thereby enhancing the understanding and comprehension of the Cebuano-Visayan discourse.
{"title":"Rules for Orthographic Word Parsing of the Philippines' Cebuano-Visayan Language Using Context-Free Grammars","authors":"Roseclaremath A. Caroro, Rolysent K. Paredes, Jerry M. Lumasag","doi":"10.4018/ijssci.2020040103","DOIUrl":"https://doi.org/10.4018/ijssci.2020040103","url":null,"abstract":"Syllabication is essential in the preprocessing stage of speech systems. In the context of the Philippines' Cebuano-Visayan language's syllabication rules, the existing rules do not include hyphenated words although the hyphen defines the syllable boundary in a word. Hence, this study created grammar rules for hyphenated words which include sequences of a hyphen between vowel-consonant, consonant-consonant, vowel-vowel, and consonant-vowel. The test was done for the enhanced grammar rules for Cebuano-Visayan syllabication with 1,465 representative hyphenated and non-hyphenated words of varying lengths. The result further implies that the syllabication analysis for hyphenated words showed that hyphens improve the naturalness and intelligibility in the utterance of the words, thereby enhancing the understanding and comprehension of the Cebuano-Visayan discourse.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115814824","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 : 2020-04-01DOI: 10.4018/ijssci.2020040101
D. Pashchenko
Competition in industry of software production as well as in IT sector has special features. Understanding current trends and complex connections between software industry and world economic development gives new ideas about competition in the IT domain. One of the key trends is digital transformation. It is supported by software, but it also has a strong impact on the software development industry and provides the new opportunities in software production and IT business change management. The main idea of the paper is total automation and a focus on measurable processes that give a continual flow of digital data that should be used on different levels of a company's management, business development, production processes, and even client's perception of the software product. Management of those core activities, based on such digital data flows, is becoming sophisticated and more flexible, based on relevant and estimated indicators. In this article, there is a multifactor analysis of digitalization in software engineering and IT business management with a focus on change management. The main results of research are demonstrating how the influence of digitalization could be used in competition.
{"title":"Digitalization in Software Engineering and IT Business","authors":"D. Pashchenko","doi":"10.4018/ijssci.2020040101","DOIUrl":"https://doi.org/10.4018/ijssci.2020040101","url":null,"abstract":"Competition in industry of software production as well as in IT sector has special features. Understanding current trends and complex connections between software industry and world economic development gives new ideas about competition in the IT domain. One of the key trends is digital transformation. It is supported by software, but it also has a strong impact on the software development industry and provides the new opportunities in software production and IT business change management. The main idea of the paper is total automation and a focus on measurable processes that give a continual flow of digital data that should be used on different levels of a company's management, business development, production processes, and even client's perception of the software product. Management of those core activities, based on such digital data flows, is becoming sophisticated and more flexible, based on relevant and estimated indicators. In this article, there is a multifactor analysis of digitalization in software engineering and IT business management with a focus on change management. The main results of research are demonstrating how the influence of digitalization could be used in competition.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126526884","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 : 2020-04-01DOI: 10.4018/ijssci.2020040102
Rinat Galiautdinov
Nowadays, drones play a significant role not only in civil ventures, but also in the military sphere. Planning the trajectories of the hives of the drones is not a trivial task and requires deep research. In this research, the author considers different strategies of biological creatures and then extrapolated on the drones. The author's research demonstrates the math model of the drones behavior in the hive, provides algorithmic architecture. The author describes in the detail the layers of the system for management of the drones and their responsibilities and architecture. The author also provides a software algorithm which demonstrates effective grouping of the drones (creating a swarm) which is later on used in the movement of the swarm.
{"title":"The Math Model of Drone Behavior in the Hive, Providing Algorithmic Architecture","authors":"Rinat Galiautdinov","doi":"10.4018/ijssci.2020040102","DOIUrl":"https://doi.org/10.4018/ijssci.2020040102","url":null,"abstract":"Nowadays, drones play a significant role not only in civil ventures, but also in the military sphere. Planning the trajectories of the hives of the drones is not a trivial task and requires deep research. In this research, the author considers different strategies of biological creatures and then extrapolated on the drones. The author's research demonstrates the math model of the drones behavior in the hive, provides algorithmic architecture. The author describes in the detail the layers of the system for management of the drones and their responsibilities and architecture. The author also provides a software algorithm which demonstrates effective grouping of the drones (creating a swarm) which is later on used in the movement of the swarm.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132185836","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 : 2019-10-01DOI: 10.4018/ijssci.2019100103
Hadj Ahmed Bouarara
Breast cancer has become a major health problem in the world over the past 50 years and its incidence has increased in recent years. It accounts for 33% of all cancer cases, and 60% of new cases of breast cancer occur in women aged 50 to 74 years. In this work we have proposed a computer-assisted diagnostic (CAD) system that can predict whether a woman has cancer or not by analyzing her mammogram automatically without passing through a biopsy stage. The screening mammogram will be vectorized using the n-gram pixel representation. After the vectors obtained will be classified into one of the classes—with cancer or without cancer—using the social elephant algorithm. The experimentation using the digital database for screening mammography (DDSM) and validation measures—f-measure entropy recall, accuracy, specificity, RCT, ROC, AUC—show clearly the effectiveness and the superiority of our proposed bioinspired technique compared to others techniques existed in the literature such as naïve bayes, Knearest neighbours, and decision tree c4.5. The goal is to help radiologists with early detection to reduce the mortality rate among women with breast cancer.
{"title":"A Computer-Assisted Diagnostic (CAD) of Screening Mammography to Detect Breast Cancer Without a Surgical Biopsy","authors":"Hadj Ahmed Bouarara","doi":"10.4018/ijssci.2019100103","DOIUrl":"https://doi.org/10.4018/ijssci.2019100103","url":null,"abstract":"Breast cancer has become a major health problem in the world over the past 50 years and its incidence has increased in recent years. It accounts for 33% of all cancer cases, and 60% of new cases of breast cancer occur in women aged 50 to 74 years. In this work we have proposed a computer-assisted diagnostic (CAD) system that can predict whether a woman has cancer or not by analyzing her mammogram automatically without passing through a biopsy stage. The screening mammogram will be vectorized using the n-gram pixel representation. After the vectors obtained will be classified into one of the classes—with cancer or without cancer—using the social elephant algorithm. The experimentation using the digital database for screening mammography (DDSM) and validation measures—f-measure entropy recall, accuracy, specificity, RCT, ROC, AUC—show clearly the effectiveness and the superiority of our proposed bioinspired technique compared to others techniques existed in the literature such as naïve bayes, Knearest neighbours, and decision tree c4.5. The goal is to help radiologists with early detection to reduce the mortality rate among women with breast cancer.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114329108","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 : 2019-10-01DOI: 10.4018/ijssci.2019100101
Yunke Li, Hongyuan Shi, Liang Chen, Fan Jiang
Convolutional neural networks (CNN) are widely used deep learning frameworks and are applied in the field of face recognition, achieving outstanding results. The Macropixel comparison approach is a shallow mathematical approach that recognizes faces by comparing the original pixel blocks of face images. In this article, the authors are inspired by ideas of the currently popular deep neural network framework and introduce two features into the mathematical approach: deep overlap and weighted filter. The aim is to explore if the idea of deep learning could benefit mathematical recognition method, which might extend the scope of face recognition research. Results from the experiments show that the new proposed approach achieves markedly better recognition rates than the original macropixel methods.
{"title":"Convolutional Approach Also Benefits Traditional Face Pattern Recognition Algorithm [208!]","authors":"Yunke Li, Hongyuan Shi, Liang Chen, Fan Jiang","doi":"10.4018/ijssci.2019100101","DOIUrl":"https://doi.org/10.4018/ijssci.2019100101","url":null,"abstract":"Convolutional neural networks (CNN) are widely used deep learning frameworks and are applied in the field of face recognition, achieving outstanding results. The Macropixel comparison approach is a shallow mathematical approach that recognizes faces by comparing the original pixel blocks of face images. In this article, the authors are inspired by ideas of the currently popular deep neural network framework and introduce two features into the mathematical approach: deep overlap and weighted filter. The aim is to explore if the idea of deep learning could benefit mathematical recognition method, which might extend the scope of face recognition research. Results from the experiments show that the new proposed approach achieves markedly better recognition rates than the original macropixel methods.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886711","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 : 2019-10-01DOI: 10.4018/ijssci.2019100102
Ravi Kumar Saidala
Emails have become one of the popular and flexible web or mobile-based applications that enables users to communicate. For decades, the most severe problem identified in email applications was unwanted emails. Electronic spam is also referred as spam emails, in which unsolicited and unwanted mails are Received. Making an email mailbox clean by detecting and eliminating all the spam mails is a challenging task. Classification-based email filtering is one of the best approaches used by many researchers to deal with the spam email filtering problem. In this work, the NOA optimization algorithm and the SVM classifier are used for getting an optimal feature subset of the Enron-spam dataset and classifying the obtained optimal feature subset. NOA is a recently developed metaheuristic algorithm which is driven by mimicking the energy saving flying pattern of the Northern Bald Ibis (Threskiornithidae). The performance comparisons have been made with other existing methods. The superiority of the proposed novel feature selection approach is evident in the analysis and comparison of the classification results.
{"title":"Northern Bald Ibis Algorithm-Based Novel Feature Selection Approach","authors":"Ravi Kumar Saidala","doi":"10.4018/ijssci.2019100102","DOIUrl":"https://doi.org/10.4018/ijssci.2019100102","url":null,"abstract":"Emails have become one of the popular and flexible web or mobile-based applications that enables users to communicate. For decades, the most severe problem identified in email applications was unwanted emails. Electronic spam is also referred as spam emails, in which unsolicited and unwanted mails are Received. Making an email mailbox clean by detecting and eliminating all the spam mails is a challenging task. Classification-based email filtering is one of the best approaches used by many researchers to deal with the spam email filtering problem. In this work, the NOA optimization algorithm and the SVM classifier are used for getting an optimal feature subset of the Enron-spam dataset and classifying the obtained optimal feature subset. NOA is a recently developed metaheuristic algorithm which is driven by mimicking the energy saving flying pattern of the Northern Bald Ibis (Threskiornithidae). The performance comparisons have been made with other existing methods. The superiority of the proposed novel feature selection approach is evident in the analysis and comparison of the classification results.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115107997","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 : 2019-07-01DOI: 10.4018/ijssci.2019070102
F. Al-akashi
In this article, we propose a neural network model to create a Wikipedia article summarization for each query to allow users to find summary of the topic without going through the whole content in the article. Often, Wikipedia returns the articles related to a search query that makes obvious finding the relevant topic for the user. Text summarization is generated by extracting all those important sentences that are most significant in its topics and have a strong match in its content. Experimentally, each sentence in the article content is encoded as a set of features and presented as an input to the network. The proposed neural network is trained using a set of randomly selected typical articles from Wikipedia. The network output is then used to predict the sentences as a summary of content from the searched query. The results showed that the proposed approach is robust and efficient at finding relevant summaries for most searched queries. Evaluation of the proposal yields accuracy scores of 0.10317 in ROUGE-N and 0.13998 in ROUGE–L.
{"title":"Abstract Retrieval over Wikipedia Articles Using Neural Network","authors":"F. Al-akashi","doi":"10.4018/ijssci.2019070102","DOIUrl":"https://doi.org/10.4018/ijssci.2019070102","url":null,"abstract":"In this article, we propose a neural network model to create a Wikipedia article summarization for each query to allow users to find summary of the topic without going through the whole content in the article. Often, Wikipedia returns the articles related to a search query that makes obvious finding the relevant topic for the user. Text summarization is generated by extracting all those important sentences that are most significant in its topics and have a strong match in its content. Experimentally, each sentence in the article content is encoded as a set of features and presented as an input to the network. The proposed neural network is trained using a set of randomly selected typical articles from Wikipedia. The network output is then used to predict the sentences as a summary of content from the searched query. The results showed that the proposed approach is robust and efficient at finding relevant summaries for most searched queries. Evaluation of the proposal yields accuracy scores of 0.10317 in ROUGE-N and 0.13998 in ROUGE–L.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127725668","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 : 2019-07-01DOI: 10.4018/ijssci.2019070103
Hao Zhou, Mengyao Zhao, Linbo Wu, Xiaohong Chen
Cyber-physical systems (CPSs) connect the cyber world with the physical world through a network of interrelated elements, such as sensors and actuators, robots, and other computing devices. Timing constraints on the interactions (timing behaviors) should be modelled and verified as cyber-physical systems are becoming more and more complex. This article proposes modeling the typical timing behaviors according to their time characteristics, periodicity, multiform time, and synchronization, and verifies them against properties using simulations. Sequence diagrams are presented for the modeling, and modelica is used for simulation. In the simulation, the time dependence relations are defined, and used for simulation parameter data automatic generation, in addition to the paths from the sequence diagrams. Finally, a Parachute System is used as an example to show the feasibility and effectiveness of the approach.
{"title":"Simulating Timing Behaviors for Cyber-Physical Systems Using Modelica","authors":"Hao Zhou, Mengyao Zhao, Linbo Wu, Xiaohong Chen","doi":"10.4018/ijssci.2019070103","DOIUrl":"https://doi.org/10.4018/ijssci.2019070103","url":null,"abstract":"Cyber-physical systems (CPSs) connect the cyber world with the physical world through a network of interrelated elements, such as sensors and actuators, robots, and other computing devices. Timing constraints on the interactions (timing behaviors) should be modelled and verified as cyber-physical systems are becoming more and more complex. This article proposes modeling the typical timing behaviors according to their time characteristics, periodicity, multiform time, and synchronization, and verifies them against properties using simulations. Sequence diagrams are presented for the modeling, and modelica is used for simulation. In the simulation, the time dependence relations are defined, and used for simulation parameter data automatic generation, in addition to the paths from the sequence diagrams. Finally, a Parachute System is used as an example to show the feasibility and effectiveness of the approach.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115329756","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 : 2019-07-01DOI: 10.4018/ijssci.2019070101
R. Bharathi, R. Selvarani
In the recent past, automotive industries are concentrating on software controlled automatic functions for its safety operations. The automotive safety and reliability lie in its design, construction, and software implementation. To assess the software reliability, the hidden design errors are classified and quantified. The temporal characteristic of numerical error is analyzed and its probabilistic behavior is explored using a novel framework called software failure estimation with numerical error (SFENE). Here, a model is devised to assess the probability of occurrence of the numerical error and its propagations from the initial to various other states using a Hidden Markov Model. It is seen that the framework SFENE supports classifying and quantifying the behavior of numerical errors while interacting across its system components and aids in the assessment on software reliability at design stage. The sensitivity and precision are found to be satisfactory. This attempt will support in the development of cost effective and error free safety critical software system.
{"title":"Software Reliability Assessment of Safety Critical System Using Computational Intelligence","authors":"R. Bharathi, R. Selvarani","doi":"10.4018/ijssci.2019070101","DOIUrl":"https://doi.org/10.4018/ijssci.2019070101","url":null,"abstract":"In the recent past, automotive industries are concentrating on software controlled automatic functions for its safety operations. The automotive safety and reliability lie in its design, construction, and software implementation. To assess the software reliability, the hidden design errors are classified and quantified. The temporal characteristic of numerical error is analyzed and its probabilistic behavior is explored using a novel framework called software failure estimation with numerical error (SFENE). Here, a model is devised to assess the probability of occurrence of the numerical error and its propagations from the initial to various other states using a Hidden Markov Model. It is seen that the framework SFENE supports classifying and quantifying the behavior of numerical errors while interacting across its system components and aids in the assessment on software reliability at design stage. The sensitivity and precision are found to be satisfactory. This attempt will support in the development of cost effective and error free safety critical software system.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"354 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121628629","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 : 2019-04-01DOI: 10.4018/IJSSCI.2019040101
Ravi Kumar Saidala, Nagaraju Devarakonda
This article proposes a new optimal data clustering method for finding optimal clusters of data by incorporating chaotic maps into the standard NOA. NOA, a newly developed optimization technique, has been shown to be efficient in generating optimal results with lowest solution cost. The incorporation of chaotic maps into metaheuristics enables algorithms to diversify the solution space into two phases: explore and exploit more. To make the NOA more efficient and avoid premature convergence, chaotic maps are incorporated in this work, termed as CNOAs. Ten different chaotic maps are incorporated individually into standard NOA for testing the optimization performance. The CNOA is first benchmarked on 23 standard functions. Secondly, testing was done on the numerical complexity of the new clustering method which utilizes CNOA, by solving 10 UCI data cluster problems and 4 web document cluster problems. The comparisons have been made with the help of obtaining statistical and graphical results. The superiority of the proposed optimal clustering algorithm is evident from the simulations and comparisons.
{"title":"A Novel Chaotic Northern Bald Ibis Optimization Algorithm for Solving Different Cluster Problems [ICCICC18 #155]","authors":"Ravi Kumar Saidala, Nagaraju Devarakonda","doi":"10.4018/IJSSCI.2019040101","DOIUrl":"https://doi.org/10.4018/IJSSCI.2019040101","url":null,"abstract":"This article proposes a new optimal data clustering method for finding optimal clusters of data by incorporating chaotic maps into the standard NOA. NOA, a newly developed optimization technique, has been shown to be efficient in generating optimal results with lowest solution cost. The incorporation of chaotic maps into metaheuristics enables algorithms to diversify the solution space into two phases: explore and exploit more. To make the NOA more efficient and avoid premature convergence, chaotic maps are incorporated in this work, termed as CNOAs. Ten different chaotic maps are incorporated individually into standard NOA for testing the optimization performance. The CNOA is first benchmarked on 23 standard functions. Secondly, testing was done on the numerical complexity of the new clustering method which utilizes CNOA, by solving 10 UCI data cluster problems and 4 web document cluster problems. The comparisons have been made with the help of obtaining statistical and graphical results. The superiority of the proposed optimal clustering algorithm is evident from the simulations and comparisons.","PeriodicalId":432255,"journal":{"name":"Int. J. Softw. Sci. Comput. Intell.","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134077156","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：