s the core modules from ontology structure and technology. All operations related to ontology management are performed by the modules in this layer. The Knowledge Base Layer contains the Customer Ontology and SWRL rule set in the knowledge base used by the system. The Database Layer contains two databases in the system. These databases are; the MongoDB database, where deduplicated data is stored, and the other is the Neo4J database, where ontology triples are stored. 3.2. The Core Modules
{"title":"An Ontology Based Approach for Next Generation Customer Relationship Management Systems","authors":"Ali Murat Tiryaki, Muhammet Atalay","doi":"10.18100/ijamec.802695","DOIUrl":"https://doi.org/10.18100/ijamec.802695","url":null,"abstract":"s the core modules from ontology structure and technology. All operations related to ontology management are performed by the modules in this layer. The Knowledge Base Layer contains the Customer Ontology and SWRL rule set in the knowledge base used by the system. The Database Layer contains two databases in the system. These databases are; the MongoDB database, where deduplicated data is stored, and the other is the Neo4J database, where ontology triples are stored. 3.2. The Core Modules","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129141201","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}
Nowadays, people raising pet animals in Turkey is increasing daily. The feeding of dogs, which are members of the houses as valuable assets, is at least as necessary as family members. Calculation of dogs' daily nutrient requirements, maintenance, growth, pregnancy, lactating, working, etc. are very variable and require an intense estimate. Feeding pet dogs only with industrially prepared foods can affect the economy of the family and the health of dogs negatively. Mainly, it is continuously questioned by the animal owners whether foods and additives that may harm health are used in industrially prepared foods. Desktop, web, and mobile-based software are used in the animal feeding area. Nevertheless, according to the researches, there is no web-based software that is used for dog diet preparation that can be used by dog owners who can calculate precisely the daily nutrient requirements of dogs and meet these requirements with available ingredients so far. The data used in this study were taken from Selcuk University, Faculty of Veterinary Medicine, Animal Science and Animal Nutrition Department. In this study, a linear programming model is proposed to calculate dog diets that both can meet the nutrient requirements of dogs and can engage cost optimization. User-friendly web-based dog diet preparation software is performed.
{"title":"Cost Optimization of Homemade Diet for Dogs","authors":"H. Joban, M. A. Şahman, F. Inal","doi":"10.18100/ijamec.828440","DOIUrl":"https://doi.org/10.18100/ijamec.828440","url":null,"abstract":"Nowadays, people raising pet animals in Turkey is increasing daily. The feeding of dogs, which are members of the houses as valuable assets, is at least as necessary as family members. Calculation of dogs' daily nutrient requirements, maintenance, growth, pregnancy, lactating, working, etc. are very variable and require an intense estimate. Feeding pet dogs only with industrially prepared foods can affect the economy of the family and the health of dogs negatively. Mainly, it is continuously questioned by the animal owners whether foods and additives that may harm health are used in industrially prepared foods. Desktop, web, and mobile-based software are used in the animal feeding area. Nevertheless, according to the researches, there is no web-based software that is used for dog diet preparation that can be used by dog owners who can calculate precisely the daily nutrient requirements of dogs and meet these requirements with available ingredients so far. The data used in this study were taken from Selcuk University, Faculty of Veterinary Medicine, Animal Science and Animal Nutrition Department. In this study, a linear programming model is proposed to calculate dog diets that both can meet the nutrient requirements of dogs and can engage cost optimization. User-friendly web-based dog diet preparation software is performed.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115662678","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}
Regulation capability of an automatic voltage regulator (AVR) system still needs to be improved to keep the output voltage of the generator within the AVR system at the desired level. Researchers have been developing new control structures and designing controllers to improve the performance of the AVR system. Designing of PID controller, which is commonly preferred controller due to its simple structure and robustness against to system parameter changes, has an important place among these studies. Especially with the development of metaheuristic algorithms, more successful PID controller designs are emerging by using these algorithms than traditional design methods. Undoubtedly, the objective function utilized also has a significant effect on this success. Therefore, effects of the objective function in PID controller design process for an AVR system are examined in this study. Two different PID controllers are designed using two different metaheuristic algorithms, namely, crow search algorithm (CSA) and ant colony optimization (ACO) algorithm. The parameters of the PID controllers are optimally tuned by using five different objective functions in both algorithms. These objective functions are: Integral of absolute error (IAE), integral of squared error (ISE), integral of time-weighted absolute error (ITAE), integral of time-weighted squared error (ITSE), and a commonly used user-defined objective function. The performance of the designed PID controllers are compared in terms of transient response characteristics and performance metrics. In addition, in order to evaluate the stability of the AVR system with the designed controllers, bode analysis, pole-zero map analysis and robustness analysis are performed.
{"title":"Effects of objective function in PID controller design for an AVR system","authors":"Seyit Ahmet Nafiz Burnaz, M. S. Ayas","doi":"10.18100/ijamec.803257","DOIUrl":"https://doi.org/10.18100/ijamec.803257","url":null,"abstract":"Regulation capability of an automatic voltage regulator (AVR) system still needs to be improved to keep the output voltage of the generator within the AVR system at the desired level. Researchers have been developing new control structures and designing controllers to improve the performance of the AVR system. Designing of PID controller, which is commonly preferred controller due to its simple structure and robustness against to system parameter changes, has an important place among these studies. Especially with the development of metaheuristic algorithms, more successful PID controller designs are emerging by using these algorithms than traditional design methods. Undoubtedly, the objective function utilized also has a significant effect on this success. Therefore, effects of the objective function in PID controller design process for an AVR system are examined in this study. Two different PID controllers are designed using two different metaheuristic algorithms, namely, crow search algorithm (CSA) and ant colony optimization (ACO) algorithm. The parameters of the PID controllers are optimally tuned by using five different objective functions in both algorithms. These objective functions are: Integral of absolute error (IAE), integral of squared error (ISE), integral of time-weighted absolute error (ITAE), integral of time-weighted squared error (ITSE), and a commonly used user-defined objective function. The performance of the designed PID controllers are compared in terms of transient response characteristics and performance metrics. In addition, in order to evaluate the stability of the AVR system with the designed controllers, bode analysis, pole-zero map analysis and robustness analysis are performed.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114775343","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}
In distributed environment, some operations related to objects are performed. For example, objects can be accessed or they can be moved. In our study, events related to objects (object-access, object-move) were created as independent events. In this study, the distributed environment simulation was performed and the effectiveness and success of the path compression algorithm, which we proposed as a result of the experimental study, was demonstrated. The purpose of this study is to show the effectiveness and benefits of the path compression algorithm. Path compression algorithm is an efficient algorithm whose runtime is linear. With the path compression, the long node chain that is formed while data objects are passing between the source node and the destination is broken, so that the objects are retrieved fast and the cost of access is reduced. This result is shown with experimental study by modeling the distributed environment. It is shown comparative the results of the distributed environment simulation according to the various Access/Move (%) rates using binomial distribution. When we use the path compression, the maximum length and mean length of the chain decreases. Thus, with the path compression algorithm, the long node chain created by the objects is broken, the cost of accessing the objects is reduced, and fast access to the objects is ensured. In short, with our study, fast access to data is ensured in a distributed environment.
{"title":"Distributed Environment Modeling using Path Compression Algorithm","authors":"Çigdem Bakir, Veli Hakkoymaz","doi":"10.18100/ijamec.797074","DOIUrl":"https://doi.org/10.18100/ijamec.797074","url":null,"abstract":"In distributed environment, some operations related to objects are performed. For example, objects can be accessed or they can be moved. In our study, events related to objects (object-access, object-move) were created as independent events. In this study, the distributed environment simulation was performed and the effectiveness and success of the path compression algorithm, which we proposed as a result of the experimental study, was demonstrated. The purpose of this study is to show the effectiveness and benefits of the path compression algorithm. Path compression algorithm is an efficient algorithm whose runtime is linear. With the path compression, the long node chain that is formed while data objects are passing between the source node and the destination is broken, so that the objects are retrieved fast and the cost of access is reduced. This result is shown with experimental study by modeling the distributed environment. It is shown comparative the results of the distributed environment simulation according to the various Access/Move (%) rates using binomial distribution. When we use the path compression, the maximum length and mean length of the chain decreases. Thus, with the path compression algorithm, the long node chain created by the objects is broken, the cost of accessing the objects is reduced, and fast access to the objects is ensured. In short, with our study, fast access to data is ensured in a distributed environment.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116605344","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}
Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.
{"title":"Performance Analysis in Multi-KPI Optimizations","authors":"Gökhan Koç","doi":"10.18100/ijamec.796351","DOIUrl":"https://doi.org/10.18100/ijamec.796351","url":null,"abstract":"Importance of resource planning at airports, ports, logistic centers and similar operation points is increasing significantly each day due to competitions, intensities and irregularities in operations. Multi-objective optimization algorithms try to reach the user defined objectives of the related operations as much as possible but the performance of these algorithms starts to differ while the number of defined Key Performance Indicators (KPI’s) are increasing. In multi-KPI optimization algorithms, there are many issues and parameters to consider which affect the optimizer performances such as; relationship between KPI’s, the number of KPI’s, number of resources, tasks. In addition, due to some specific business rules in the operation, not every resource can be assigned to every task and the optimization algorithm needs to consider these rules when generating allocation plan. Within the scope of this study, an optimization algorithm which is developed by TAV Technologies is used to analysis optimizer performance changes according to the number of defined KPI’s. For the same resource and task group, the optimization algorithm configured with different KPI combinations and run repeatedly. Except for the KPI definitions, all other optimizer inputs were kept constant in all tests and the results were compared with each other. Specific business rules were ignored in this study to analysis test results clearly.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133540972","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}
Ali Saglam, H. B. Makineci, Ö. K. Baykan, N. Baykan
Processing of 3D point cloud data is seen as a problem due to the difficulties of processing millions of unstructured points. The point cloud segmentation process is a crucial pre-classification stage such that it reduces the high processing time required to extract meaningful information from raw data and produces some distinctive features for the classification stage. Local surface inclinations of objects are the most effective features of 3D point clouds to provide meaningful information about the objects. Sampling the points into sub-volumes (voxels) is a technique commonly used in the literature to obtain the required neighboring point groups to calculate local surface directions (with normal vectors). The graph-based segmentation approaches are widely used for the surface segmentation using the attributes of the local surface orientations and continuities. In this study, only two geometrical primitives which are normal vectors and barycenters of point groups are used to weight the connections between the adjacent voxels (vertices). The defined 14 possible dissimilarity calculations of three angular values getting from the primitives are experimented and evaluated on five sample datasets that have reference data for segmentation. Finally, the results of the measures are compared in terms of accuracy and F1 score. According to the results, the weight measure W7 (seventh calculation) gives 0.8026 accuracy and 0.7305 F1 score with higher standard deviations, while the original weight measure (W8) of the segmentation method gives 0.7890 accuracy and 0.6774 F1 score with lower standard deviations. BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)
{"title":"Dissimilarity weighting for graph-based point cloud segmentation using local surface gradients","authors":"Ali Saglam, H. B. Makineci, Ö. K. Baykan, N. Baykan","doi":"10.18100/ijamec.802893","DOIUrl":"https://doi.org/10.18100/ijamec.802893","url":null,"abstract":"Processing of 3D point cloud data is seen as a problem due to the difficulties of processing millions of unstructured points. The point cloud segmentation process is a crucial pre-classification stage such that it reduces the high processing time required to extract meaningful information from raw data and produces some distinctive features for the classification stage. Local surface inclinations of objects are the most effective features of 3D point clouds to provide meaningful information about the objects. Sampling the points into sub-volumes (voxels) is a technique commonly used in the literature to obtain the required neighboring point groups to calculate local surface directions (with normal vectors). The graph-based segmentation approaches are widely used for the surface segmentation using the attributes of the local surface orientations and continuities. In this study, only two geometrical primitives which are normal vectors and barycenters of point groups are used to weight the connections between the adjacent voxels (vertices). The defined 14 possible dissimilarity calculations of three angular values getting from the primitives are experimented and evaluated on five sample datasets that have reference data for segmentation. Finally, the results of the measures are compared in terms of accuracy and F1 score. According to the results, the weight measure W7 (seventh calculation) gives 0.8026 accuracy and 0.7305 F1 score with higher standard deviations, while the original weight measure (W8) of the segmentation method gives 0.7890 accuracy and 0.6774 F1 score with lower standard deviations. BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0/)","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124836166","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}
In this paper, a modified (proportional-integral) PI control is suggested to improve current tracking performance of three-phase grid-tied inverters (GTI). Presence of the L filter between inverter and grid, makes complex to design a controller with proper parameters, due to characteristics of the filter. Clasical PI control depends on an accurate dynamical model, thus its performance is deteriorated by parametric uncertainties, unmodelled dynamics and external disturbances, when operating conditions affect the filter parameters. To solve this problem, uncertainty and disturbance estimator based PI current control approach is proposed for grid-tied inverters, which provides robustness against to parametric perturbations. An UDE based observer that has been adopted into the PI current loop is used to eliminate lumped disturbances and the steady-state tracking error of current states, which can enhance the robustness of the control performance. Then, parameter design method, stability and robustness analysis are explored and presented. Performance comparison among the clasical PI and proposed control scheme. Efficacy and performance of the proposed approach are carried out by simulations and experiments. Experimental results show that effectiveness of the suggested control method against parametric uncertainties and disturbances are succesfully validated. Besides, the precise current tracking performance with zero steady state error has been reached.
{"title":"UDE Based Robust Control of Grid Tied Inverters","authors":"Akın Uslu","doi":"10.18100/ijamec.803545","DOIUrl":"https://doi.org/10.18100/ijamec.803545","url":null,"abstract":"In this paper, a modified (proportional-integral) PI control is suggested to improve current tracking performance of three-phase grid-tied inverters (GTI). Presence of the L filter between inverter and grid, makes complex to design a controller with proper parameters, due to characteristics of the filter. Clasical PI control depends on an accurate dynamical model, thus its performance is deteriorated by parametric uncertainties, unmodelled dynamics and external disturbances, when operating conditions affect the filter parameters. To solve this problem, uncertainty and disturbance estimator based PI current control approach is proposed for grid-tied inverters, which provides robustness against to parametric perturbations. An UDE based observer that has been adopted into the PI current loop is used to eliminate lumped disturbances and the steady-state tracking error of current states, which can enhance the robustness of the control performance. Then, parameter design method, stability and robustness analysis are explored and presented. Performance comparison among the clasical PI and proposed control scheme. Efficacy and performance of the proposed approach are carried out by simulations and experiments. Experimental results show that effectiveness of the suggested control method against parametric uncertainties and disturbances are succesfully validated. Besides, the precise current tracking performance with zero steady state error has been reached.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123624702","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}
Yavuz Selim Taspinar, M. M. Saritas, Ilkay Cinar, M. Koklu
The rapid advancement of today's technologies, it is tried to facilitate whichever system will be used by using voice features such as person recognition and speech recognition by making use of the voices of the users. Organizations serving in these systems need less manpower and facilitate the operation by helping users faster. The decision-making process using sound features is a very challenging process. With gender recognition, which is one of these steps, it is possible to address the user by gender. In this study, it is aimed to define the genders according to the voices in terms of both forensic informatics and the rapid and accurate progress of the processes. In this study, 3168 male and female voice samples were taken as a dataset. Sound samples were first analyzed by acoustic analysis in R using seewave and tuneR packages. Artificial neural networks were used in the classification stage. In order to increase the classification accuracy, the dataset was divided into 10 parts and each part was excluded from training for testing and used for retesting. Average classification success was found by taking the arithmetic mean of the results. In the classification made with artificial neural networks, male and female voices could be distinguished from each other with a success of 97.9%.
{"title":"Gender Determination Using Voice Data","authors":"Yavuz Selim Taspinar, M. M. Saritas, Ilkay Cinar, M. Koklu","doi":"10.18100/ijamec.809476","DOIUrl":"https://doi.org/10.18100/ijamec.809476","url":null,"abstract":"The rapid advancement of today's technologies, it is tried to facilitate whichever system will be used by using voice features such as person recognition and speech recognition by making use of the voices of the users. Organizations serving in these systems need less manpower and facilitate the operation by helping users faster. The decision-making process using sound features is a very challenging process. With gender recognition, which is one of these steps, it is possible to address the user by gender. In this study, it is aimed to define the genders according to the voices in terms of both forensic informatics and the rapid and accurate progress of the processes. In this study, 3168 male and female voice samples were taken as a dataset. Sound samples were first analyzed by acoustic analysis in R using seewave and tuneR packages. Artificial neural networks were used in the classification stage. In order to increase the classification accuracy, the dataset was divided into 10 parts and each part was excluded from training for testing and used for retesting. Average classification success was found by taking the arithmetic mean of the results. In the classification made with artificial neural networks, male and female voices could be distinguished from each other with a success of 97.9%.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131661757","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}
version of this paper was presented at 9th International Conference on Advanced Technologies (ICAT'20), 10-12 August 2020, Istanbul, Turkey with the title of “Follicle Detection in Polycystic Ovary Syndrome with Image Processing Methods”.
{"title":"Follicle Detection for Polycystic Ovary Syndrome by using Image Processing Methods","authors":"P. Yilmaz, Güzin Özmen","doi":"10.18100/ijamec.803400","DOIUrl":"https://doi.org/10.18100/ijamec.803400","url":null,"abstract":"version of this paper was presented at 9th International Conference on Advanced Technologies (ICAT'20), 10-12 August 2020, Istanbul, Turkey with the title of “Follicle Detection in Polycystic Ovary Syndrome with Image Processing Methods”.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129436427","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}
Olawumi Olasunkanmi, O. D. Olanloye, Abdulquadri Adegbiji
The world is now in the era of big data and processing, and exploring the data has become one of the significant challenges. Hence, researchers have done a lot to analyse these data in the health sector to enhance disease detection and classification using artificial intelligence and ML principles. Kidney disease is one of the terrible conditions in which its late detection has sent many people to untimely graves. ML classifiers have been employed in many dimensions to classify heart disease, but, existing works have not explored the variants of each method for selection of best model parameters. An attempt is being made in this research to study the behaviour of three (3) variants each from two(2) tree-based models in the classification of Kidney Disease. Three of the variants are Complex, Medium and Simple models of Decision tree classifier and the other one are Boosted, Bagged and RUSBoosted of Ensemble Classifiers. Using MATLAB for implementation, the model performance established that the accuracy of Ensemble Classifier (Bagged tree model) is the best, concerning the speed, Decision tree (Complex and Simple tree models have the same and highest value). Hence, the two are the best. In terms of training time, Decision tree(Simple tree) has the least time and therefore the best.
{"title":"Comparison analysis of decision tree and ensemble models in the classification of chronic kidney diseases","authors":"Olawumi Olasunkanmi, O. D. Olanloye, Abdulquadri Adegbiji","doi":"10.18100/ijamec.792863","DOIUrl":"https://doi.org/10.18100/ijamec.792863","url":null,"abstract":"The world is now in the era of big data and processing, and exploring the data has become one of the significant challenges. Hence, researchers have done a lot to analyse these data in the health sector to enhance disease detection and classification using artificial intelligence and ML principles. Kidney disease is one of the terrible conditions in which its late detection has sent many people to untimely graves. ML classifiers have been employed in many dimensions to classify heart disease, but, existing works have not explored the variants of each method for selection of best model parameters. An attempt is being made in this research to study the behaviour of three (3) variants each from two(2) tree-based models in the classification of Kidney Disease. Three of the variants are Complex, Medium and Simple models of Decision tree classifier and the other one are Boosted, Bagged and RUSBoosted of Ensemble Classifiers. Using MATLAB for implementation, the model performance established that the accuracy of Ensemble Classifier (Bagged tree model) is the best, concerning the speed, Decision tree (Complex and Simple tree models have the same and highest value). Hence, the two are the best. In terms of training time, Decision tree(Simple tree) has the least time and therefore the best.","PeriodicalId":120305,"journal":{"name":"International Journal of Applied Mathematics Electronics and Computers","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132593687","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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