Pub Date : 2020-06-01DOI: 10.1109/HORA49412.2020.9152892
Gökhan Tezcan, S. Solak
Özetçe-Tarim, dünyada ve ülkemizde önemli bir emisyon kaynağidir.Büyüyen küresel nüfus, gida tüketiminin arttirmakta ve tarimsal üretim sistemleri üzerinde artan bir baski oluşturmaktadir.TÜİK tarafından 2019’da açıklanan bilgilere göre Türkiye’deki CH4 emisyonlarinin %62,3’lük ve N2O emisyonlaımm ise %71’lik payi tarimsal faaliyetlerden kaynaklanmaktadır.Bu çalışmada Hükümetler Arası iklim Değişikliği Panelinin Değerlendirme Raporlarında çeşitli analizlerin temelini oluşturmasi ve küresel düzeydeki emisyon envanterleri için önemli bir bilgi kaynağı olması sebebiyle, tarım kaynaklı sera gazı emisyon tahminlerini içeren FAOSTAT veri seti kullanilmıçtır.Çalışmanin içeriğinde FAOSTAT veri setindeki tarımsal ürünlerin besin türlerine göre smıflandırılmış ekim alanları ile CH4 ve N2O gazlarının emisyonları arasında varyans analizinden (ANOVA) de faydalanarak deney tasarımı (DOE) oluşturulmuştur.Bu deney tasarımı sonucunda emisyonlar ile ekimi yapilan besin türleri arasındaki ilişki incelenmiştir.Çeşitli besin türlerinin ekilmesi sonucunda oluşan gaz emisyonları hakkında tahminler yürütülmüştür.Yapılan çalişma sonucunda CH4 emisyonunun en çok meyve üretiminden, N2O emisyonunun ise sebze ürünlerinin üretilmesinden kaynaklandığı, meyve ve sebze üretiminin diğer ürünlere göre çevreye daha çok gaz salınımı gerçekleştirdiği sonucuna ulaşılmıştır.Agriculture is an important emission source in the world and in our country.The growing global population increases food consumption and creates an increasing pressure on agricultural production systems.According to TUIK reports in 2019, as a result of agricultural activities occurring in Turkey, CH4 and N2O emissions are 62.3% and 71%, respectively.In this study, FAOSTAT dataset containing agricultural greenhouse gas emission estimates was used.It is also used in the evaluation reports of the Intergovernmental Panel on Climate Change to form the basis of various analyzes and emission inventories at the global level.In the content of the study, the design of experiment (DoE) was created by making use of variance analysis (ANOVA) between cultivation areas classified according to food types of agricultural products in FAOSTAT data set and emissions of CH4 and N2O gases.As a result of DoE, the relationship between emissions and cultivated food types was examined.The article also made predictions about the gas emissions that occurred as a result of planting various types of food.As a result of the study, it was concluded that CH4 emission is mostly caused by fruit production, and N2O emission is caused by the production of vegetable products, and fruit and vegetable production emits more gas to the environment than other agricultural products.
{"title":"An Investigation of the Relationship between Agricultural Production and Greenhouse Gas Emissions","authors":"Gökhan Tezcan, S. Solak","doi":"10.1109/HORA49412.2020.9152892","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152892","url":null,"abstract":"Özetçe-Tarim, dünyada ve ülkemizde önemli bir emisyon kaynağidir.Büyüyen küresel nüfus, gida tüketiminin arttirmakta ve tarimsal üretim sistemleri üzerinde artan bir baski oluşturmaktadir.TÜİK tarafından 2019’da açıklanan bilgilere göre Türkiye’deki CH4 emisyonlarinin %62,3’lük ve N2O emisyonlaımm ise %71’lik payi tarimsal faaliyetlerden kaynaklanmaktadır.Bu çalışmada Hükümetler Arası iklim Değişikliği Panelinin Değerlendirme Raporlarında çeşitli analizlerin temelini oluşturmasi ve küresel düzeydeki emisyon envanterleri için önemli bir bilgi kaynağı olması sebebiyle, tarım kaynaklı sera gazı emisyon tahminlerini içeren FAOSTAT veri seti kullanilmıçtır.Çalışmanin içeriğinde FAOSTAT veri setindeki tarımsal ürünlerin besin türlerine göre smıflandırılmış ekim alanları ile CH4 ve N2O gazlarının emisyonları arasında varyans analizinden (ANOVA) de faydalanarak deney tasarımı (DOE) oluşturulmuştur.Bu deney tasarımı sonucunda emisyonlar ile ekimi yapilan besin türleri arasındaki ilişki incelenmiştir.Çeşitli besin türlerinin ekilmesi sonucunda oluşan gaz emisyonları hakkında tahminler yürütülmüştür.Yapılan çalişma sonucunda CH4 emisyonunun en çok meyve üretiminden, N2O emisyonunun ise sebze ürünlerinin üretilmesinden kaynaklandığı, meyve ve sebze üretiminin diğer ürünlere göre çevreye daha çok gaz salınımı gerçekleştirdiği sonucuna ulaşılmıştır.Agriculture is an important emission source in the world and in our country.The growing global population increases food consumption and creates an increasing pressure on agricultural production systems.According to TUIK reports in 2019, as a result of agricultural activities occurring in Turkey, CH4 and N2O emissions are 62.3% and 71%, respectively.In this study, FAOSTAT dataset containing agricultural greenhouse gas emission estimates was used.It is also used in the evaluation reports of the Intergovernmental Panel on Climate Change to form the basis of various analyzes and emission inventories at the global level.In the content of the study, the design of experiment (DoE) was created by making use of variance analysis (ANOVA) between cultivation areas classified according to food types of agricultural products in FAOSTAT data set and emissions of CH4 and N2O gases.As a result of DoE, the relationship between emissions and cultivated food types was examined.The article also made predictions about the gas emissions that occurred as a result of planting various types of food.As a result of the study, it was concluded that CH4 emission is mostly caused by fruit production, and N2O emission is caused by the production of vegetable products, and fruit and vegetable production emits more gas to the environment than other agricultural products.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128867340","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152896
Secil Genc, S. Karagol
Detection of new faults in the transformer early is very important to prevent accidents and to reduce the related material losses. Dissolved gas analysis (DGA) is widely used for this purpose. There are methods according to different standards for DGA. Conventional methods used in the implementation of DGA are improved by using intelligent systems.In this study, IEC ratio method, one of the classical methods, were used. A intelligent fuzzy-based analysis was done using MATLAB. The results obtained from fuzzy logic and real faults are given in the table and a comparative evaluation of the IEC methods is made.
{"title":"Fuzzy Logic Application in DGA Methods to Classify Fault Type in Power Transformer","authors":"Secil Genc, S. Karagol","doi":"10.1109/HORA49412.2020.9152896","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152896","url":null,"abstract":"Detection of new faults in the transformer early is very important to prevent accidents and to reduce the related material losses. Dissolved gas analysis (DGA) is widely used for this purpose. There are methods according to different standards for DGA. Conventional methods used in the implementation of DGA are improved by using intelligent systems.In this study, IEC ratio method, one of the classical methods, were used. A intelligent fuzzy-based analysis was done using MATLAB. The results obtained from fuzzy logic and real faults are given in the table and a comparative evaluation of the IEC methods is made.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127820443","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152884
Georgi Krastev, V. Voinohovska
Data organization and program realization of portal for smart mobile application for public transport schedules has been presented in this article. Realization is of PHP and DBSM (data base system management) - MySQL’s.
{"title":"Smart mobile application for public transport schedules – data organization and program realization","authors":"Georgi Krastev, V. Voinohovska","doi":"10.1109/HORA49412.2020.9152884","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152884","url":null,"abstract":"Data organization and program realization of portal for smart mobile application for public transport schedules has been presented in this article. Realization is of PHP and DBSM (data base system management) - MySQL’s.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121390720","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152865
Ilknur Aktemur, Kübra Erensoy, Emre Kocyigit
With the growth of population, there is an inevitable increase in solid waste especially in urban areas. For the municipalities, especially in smart cities, this becomes a major problem in nature, and it leads to many socio-economic and environmental problems. Thus, lowering our living standards. To eliminate or minimize these problems, using the Internet of Things (IOT) technology is the most advantageous solution for collecting solid wastes within this scope. In this paper, we proposed an optimal waste collection mechanism with the use of some IoT devices in the garbage cans which show the level of waste in them. For testing the proposal, we select a sample environment as a specific region of Istanbul, which is named as Bakirkoy. With the use of sensors, it is aimed to detect which cans are needed to be visited. Then with the use of an evolutionary algorithm, Genetic Algorithm, best path for visiting these cans can be planned in a very short time. By using this approach, it is aimed to effectively use the workforce/resources of the smart cities and making less traffic jam on the roads. Experimental results showed that the proposed system results very good enhancement in the waste collection operations.
{"title":"Optimization of Waste Collection in Smart Cities with the use of Evolutionary Algorithms","authors":"Ilknur Aktemur, Kübra Erensoy, Emre Kocyigit","doi":"10.1109/HORA49412.2020.9152865","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152865","url":null,"abstract":"With the growth of population, there is an inevitable increase in solid waste especially in urban areas. For the municipalities, especially in smart cities, this becomes a major problem in nature, and it leads to many socio-economic and environmental problems. Thus, lowering our living standards. To eliminate or minimize these problems, using the Internet of Things (IOT) technology is the most advantageous solution for collecting solid wastes within this scope. In this paper, we proposed an optimal waste collection mechanism with the use of some IoT devices in the garbage cans which show the level of waste in them. For testing the proposal, we select a sample environment as a specific region of Istanbul, which is named as Bakirkoy. With the use of sensors, it is aimed to detect which cans are needed to be visited. Then with the use of an evolutionary algorithm, Genetic Algorithm, best path for visiting these cans can be planned in a very short time. By using this approach, it is aimed to effectively use the workforce/resources of the smart cities and making less traffic jam on the roads. Experimental results showed that the proposed system results very good enhancement in the waste collection operations.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127141594","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152880
Seyed Mohammad Yasoubi, Y. Farzaneh, Javad Ghanbarian, Seyed Amirhossein Mousavi
The aim of this study is to provide a central pattern generator (CPG) method that can be used to control the lower limbs and use the exoskeleton robot. The generator is based on Winter book formulas and articles written in this field and created in some parts. In order to reproduce the correct rhythmic movements of the knee angles to the pelvis and the angles of the knees to the ankles and to help the rhythmic cycle of the healthy leg for the defective leg in the network (CPG) was calculated using nonlinear differential equations. Using a change in the parameters of the control system, he used it to control the lower limbs and help different types of anomalies in walking in patients with various motor disorders. (Using the data obtained from the pattern of the person with the insufficiency in one of the legs and using the healthy foot pattern of the same person, the walking simulation model / experimental data presented,) were developed and the simulation results Numbers can be suggested as tips to further improve the model and use it to control the lower limbs and exoskeleton robots. Rhythmic patterns may be used to plan the path of various robot systems, such as exoskeletons and animal robots, and other such robots.
{"title":"Production of CPG pathways for lower limbs with the ability to change routes online","authors":"Seyed Mohammad Yasoubi, Y. Farzaneh, Javad Ghanbarian, Seyed Amirhossein Mousavi","doi":"10.1109/HORA49412.2020.9152880","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152880","url":null,"abstract":"The aim of this study is to provide a central pattern generator (CPG) method that can be used to control the lower limbs and use the exoskeleton robot. The generator is based on Winter book formulas and articles written in this field and created in some parts. In order to reproduce the correct rhythmic movements of the knee angles to the pelvis and the angles of the knees to the ankles and to help the rhythmic cycle of the healthy leg for the defective leg in the network (CPG) was calculated using nonlinear differential equations. Using a change in the parameters of the control system, he used it to control the lower limbs and help different types of anomalies in walking in patients with various motor disorders. (Using the data obtained from the pattern of the person with the insufficiency in one of the legs and using the healthy foot pattern of the same person, the walking simulation model / experimental data presented,) were developed and the simulation results Numbers can be suggested as tips to further improve the model and use it to control the lower limbs and exoskeleton robots. Rhythmic patterns may be used to plan the path of various robot systems, such as exoskeletons and animal robots, and other such robots.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127965900","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152869
I. Draganov, S. Stefanova
This paper discusses the problem of communication between two common types of systems - resource planning and automated transport control. There still are no strict standards for data exchange between them. The configuration of automated transport systems is an overly complex and specific process that cannot be performed by non-specialists in the field. The aim of this paper is to present an architecture that integrates the two types of systems, and to establish a basic standard for communication and interaction.
{"title":"A solution for optimizing the integration of AGV systems in enterprises which are using ERP systems","authors":"I. Draganov, S. Stefanova","doi":"10.1109/HORA49412.2020.9152869","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152869","url":null,"abstract":"This paper discusses the problem of communication between two common types of systems - resource planning and automated transport control. There still are no strict standards for data exchange between them. The configuration of automated transport systems is an overly complex and specific process that cannot be performed by non-specialists in the field. The aim of this paper is to present an architecture that integrates the two types of systems, and to establish a basic standard for communication and interaction.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133769646","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152929
Abdulsamad Kurd, Nurettin Besli
With the fast progression of the internet, information security is becoming more important every day in data transmission and storage. Protecting digital data and maintaining information security have been achieved through the use of cryptographic algorithms. Most popular cryptographic algorithms are the Advanced Encryption Standard (AES) and Data Encryption Standard (DES). Encryption operation changes a plain text data to distorted data called ciphertext. The original text can be retrieved with a special key from the ciphertext. This study aims to analyze cryptographic algorithms on hardware solutions. Application-Specific Integrated Circuits (ASICs) and Field Programmable Gate Arrays (FPGAs) have been used to produce crypto-processors. In this study, the chosen algorithms are implemented on FPGAs due to their fast and easy programming capabilities. We have used the Xilinx ISE synthesis tool, ModelSim SE simulation tool, and Xilinx Spartan-6 FPGA platforms for implementation and functionality verification of the designed circuits. FPGA based implementation of AES and DES algorithms are compared in terms of Speed, Memory, and Processing Time. Study results show that AES needs less processing time than DES does for embedded and portable applications.
{"title":"Analysis of the Cryptography Methods for Design of Crypto-Processor","authors":"Abdulsamad Kurd, Nurettin Besli","doi":"10.1109/HORA49412.2020.9152929","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152929","url":null,"abstract":"With the fast progression of the internet, information security is becoming more important every day in data transmission and storage. Protecting digital data and maintaining information security have been achieved through the use of cryptographic algorithms. Most popular cryptographic algorithms are the Advanced Encryption Standard (AES) and Data Encryption Standard (DES). Encryption operation changes a plain text data to distorted data called ciphertext. The original text can be retrieved with a special key from the ciphertext. This study aims to analyze cryptographic algorithms on hardware solutions. Application-Specific Integrated Circuits (ASICs) and Field Programmable Gate Arrays (FPGAs) have been used to produce crypto-processors. In this study, the chosen algorithms are implemented on FPGAs due to their fast and easy programming capabilities. We have used the Xilinx ISE synthesis tool, ModelSim SE simulation tool, and Xilinx Spartan-6 FPGA platforms for implementation and functionality verification of the designed circuits. FPGA based implementation of AES and DES algorithms are compared in terms of Speed, Memory, and Processing Time. Study results show that AES needs less processing time than DES does for embedded and portable applications.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133845090","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152601
Buket Geyik, Medine Kara
Traffic, which became a part of our lives with the spread of cars, brought accidents and death with it. Safety and accident issues are a global problem in the world. This study aims to establish models to predict the accident severity levels of traffic accident injury records for possible accidents by using some data mining classification methods. The dataset used for this work is named Stats19, which has the traffic accident data from 2010 to 2012 in United Kingdom (UK), and it is collected by the UK government data service. The dataset was classified into three accident severity categories, which are fatal, serious, and slight. Classification algorithms use prior knowledge as training data to classify data objects into groups, which is good for us to work with. The models that we used are Multi-layer Perceptron (MLP), Decision Tree classifier, and Random Forest classifier and Naive Bayes classifier. The data extracted from the dataset will make sense to compare and predict a level degree. The tested classification algorithms come up with the results, the decision tree algorithm with an accuracy of 80.74%, the random forest classifier with an accuracy of 85.19%, the Naive Bayes algorithm with an accuracy of 83.40% and the MLP model with an accuracy of 86.67%. These factors of accidents can be important for estimating accident costs, increasing safety, and determining a strategy. Although it is not possible to stop accidents, it aims to reduce injury levels. This study is written in python programming language using Spyder integrated development environment (IDE).
{"title":"Severity Prediction with Machine Learning Methods","authors":"Buket Geyik, Medine Kara","doi":"10.1109/HORA49412.2020.9152601","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152601","url":null,"abstract":"Traffic, which became a part of our lives with the spread of cars, brought accidents and death with it. Safety and accident issues are a global problem in the world. This study aims to establish models to predict the accident severity levels of traffic accident injury records for possible accidents by using some data mining classification methods. The dataset used for this work is named Stats19, which has the traffic accident data from 2010 to 2012 in United Kingdom (UK), and it is collected by the UK government data service. The dataset was classified into three accident severity categories, which are fatal, serious, and slight. Classification algorithms use prior knowledge as training data to classify data objects into groups, which is good for us to work with. The models that we used are Multi-layer Perceptron (MLP), Decision Tree classifier, and Random Forest classifier and Naive Bayes classifier. The data extracted from the dataset will make sense to compare and predict a level degree. The tested classification algorithms come up with the results, the decision tree algorithm with an accuracy of 80.74%, the random forest classifier with an accuracy of 85.19%, the Naive Bayes algorithm with an accuracy of 83.40% and the MLP model with an accuracy of 86.67%. These factors of accidents can be important for estimating accident costs, increasing safety, and determining a strategy. Although it is not possible to stop accidents, it aims to reduce injury levels. This study is written in python programming language using Spyder integrated development environment (IDE).","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133168752","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152839
Ebru Idman, Emrah Idman, Osman Yildirim
When meteorological data such as temperature, precipitation, weather events and economic data such as stock prices and exchange rates reach large levels, it may be necessary to analyze them with time series analysis methods. The aim of this research is to analyze the data of solar power plants with time series and make predictions for the future. To achieve this goal, solar panel data with historical depth will be collected, the collected data will be trained and predicted by various time series analysis methods and comparison will be made according to the prediction success among the related models. Methodology: With this study, using Python 3.6 and R 3.6.1, the time series estimation models were modeled with AR, ARMA, SARIMA, DES and TES, the difference between the real value and the predicted value of the data was found by the RMSE (Square Root of the Mean Square Error) method and it was seen which model has the best ability to estimate the dataset. In addition, with the trend and seasonality of the data, detailed information about the dataset was obtained with descriptive analysis and graphics. As a result, it was seen that using SARIMA or TES models in the datasets that show seasonal change in the light of the studies and estimations performed gives better results.
{"title":"Estimating Solar Power Plant Data Using Time Series Analysis Methods","authors":"Ebru Idman, Emrah Idman, Osman Yildirim","doi":"10.1109/HORA49412.2020.9152839","DOIUrl":"https://doi.org/10.1109/HORA49412.2020.9152839","url":null,"abstract":"When meteorological data such as temperature, precipitation, weather events and economic data such as stock prices and exchange rates reach large levels, it may be necessary to analyze them with time series analysis methods. The aim of this research is to analyze the data of solar power plants with time series and make predictions for the future. To achieve this goal, solar panel data with historical depth will be collected, the collected data will be trained and predicted by various time series analysis methods and comparison will be made according to the prediction success among the related models. Methodology: With this study, using Python 3.6 and R 3.6.1, the time series estimation models were modeled with AR, ARMA, SARIMA, DES and TES, the difference between the real value and the predicted value of the data was found by the RMSE (Square Root of the Mean Square Error) method and it was seen which model has the best ability to estimate the dataset. In addition, with the trend and seasonality of the data, detailed information about the dataset was obtained with descriptive analysis and graphics. As a result, it was seen that using SARIMA or TES models in the datasets that show seasonal change in the light of the studies and estimations performed gives better results.","PeriodicalId":166917,"journal":{"name":"2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115629592","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 : 2020-06-01DOI: 10.1109/HORA49412.2020.9152854
Alaa Hamid Mohammed, Ahmed Muhi Shantaf, Mohammed Khalaf
Versatile correspondence framework. Reflection happens when an electromagnetic wave faces an article a lot bigger than the recurrence of an electromagnetic wave. The quality picked up (or its extra catastrophe) is commonly the most significant parameter anticipated from enormous scope engendering models that rely upon the material study of reflection. In this article, we draw an end that isn't equivalent to topical posts. Trigonometric vectors from the vector E_TOT (d), the got vitality can be yield.
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