2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)最新文献
Pub Date : 2017-08-29DOI: 10.1109/SNPD.2017.8022718
M. Shuto, H. Washizaki, K. Kakehi, Y. Fukazawa, Shoso Yamato, Masashi Okubo, B. Tenbergen
Although working in teams is an effective method for students to learn skills necessary for information systems, the optimal combination of team members to maximize the learning effectiveness has yet to be clarified. This study investigates the relationship between the combination of students' personality characteristics and learning effectiveness in three information system lecture courses. Two Five Factor Model (FFM) questionnaires were used to determine each student's personality characteristic. For each course, which has different styles, several different relationships are found. This study should assist educators in maximizing students' learning effectiveness in information systems courses involving teamwork.
{"title":"Relationship between the five factor model personality and learning effectiveness of teams in three information systems education courses","authors":"M. Shuto, H. Washizaki, K. Kakehi, Y. Fukazawa, Shoso Yamato, Masashi Okubo, B. Tenbergen","doi":"10.1109/SNPD.2017.8022718","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022718","url":null,"abstract":"Although working in teams is an effective method for students to learn skills necessary for information systems, the optimal combination of team members to maximize the learning effectiveness has yet to be clarified. This study investigates the relationship between the combination of students' personality characteristics and learning effectiveness in three information system lecture courses. Two Five Factor Model (FFM) questionnaires were used to determine each student's personality characteristic. For each course, which has different styles, several different relationships are found. This study should assist educators in maximizing students' learning effectiveness in information systems courses involving teamwork.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121345019","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 : 2017-08-29DOI: 10.1109/SNPD.2017.8022741
A. A. Gozali, S. Fujimura
Genetic algorithm (GA) is one of the standard solutions to solve many optimization problems. One of a GA type used for solving a case is island model GA (IMGA). Localization strategy is a brand-new feature for IMGA to better preserves its diversity. In the previous research, localization strategy could carry out 3SAT problem almost perfectly. In this study, the proposed feature is aimed to solve real parameter single objective computationally expensive optimization problems. Differ with an issue in previous research which has a prior knowledge and binary, the computationally expensive optimization has not any prior knowledge and floating type problem. Therefore, the localization strategy and its GA cores must adapt. The primary goal of this research is to analyze further the localization strategy for IMGA's performance. The experiments show that the new feature is successfully modified to meet the new requirement. Localization strategy for IMGA can solve all computationally expensive functions consistently. Moreover, this new feature could make IMGA reaches leading ratio 0.47 among other current solvers.
{"title":"Performance analysis of localization strategy for island model genetic algorithm","authors":"A. A. Gozali, S. Fujimura","doi":"10.1109/SNPD.2017.8022741","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022741","url":null,"abstract":"Genetic algorithm (GA) is one of the standard solutions to solve many optimization problems. One of a GA type used for solving a case is island model GA (IMGA). Localization strategy is a brand-new feature for IMGA to better preserves its diversity. In the previous research, localization strategy could carry out 3SAT problem almost perfectly. In this study, the proposed feature is aimed to solve real parameter single objective computationally expensive optimization problems. Differ with an issue in previous research which has a prior knowledge and binary, the computationally expensive optimization has not any prior knowledge and floating type problem. Therefore, the localization strategy and its GA cores must adapt. The primary goal of this research is to analyze further the localization strategy for IMGA's performance. The experiments show that the new feature is successfully modified to meet the new requirement. Localization strategy for IMGA can solve all computationally expensive functions consistently. Moreover, this new feature could make IMGA reaches leading ratio 0.47 among other current solvers.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116054895","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 : 2017-08-29DOI: 10.1109/SNPD.2017.8022717
Taketo Tsunoda, H. Washizaki, Y. Fukazawa, S. Inoue, Y. Hanai, Masanobu Kanazawa
Previous studies have researched how developer experience affects code quality, but they ignore work difficulty, although experienced developers are more likely to work on the more complex parts of a project. To examine work difficulty, we focus on revised files. Using product metrics, we evaluate file complexity in each type of file origin. Specifically, we analyze three large commercial projects (each project has about 250,000 LOC) executed by the same organization to analyze the relationship between previous project experience and developer's work. Although experienced developers do not always work on more complicated files, they introduce fewer defects, especially if the difference in work difficulty is not significant.
{"title":"Evaluating the work of experienced and inexperienced developers considering work difficulty in sotware development","authors":"Taketo Tsunoda, H. Washizaki, Y. Fukazawa, S. Inoue, Y. Hanai, Masanobu Kanazawa","doi":"10.1109/SNPD.2017.8022717","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022717","url":null,"abstract":"Previous studies have researched how developer experience affects code quality, but they ignore work difficulty, although experienced developers are more likely to work on the more complex parts of a project. To examine work difficulty, we focus on revised files. Using product metrics, we evaluate file complexity in each type of file origin. Specifically, we analyze three large commercial projects (each project has about 250,000 LOC) executed by the same organization to analyze the relationship between previous project experience and developer's work. Although experienced developers do not always work on more complicated files, they introduce fewer defects, especially if the difference in work difficulty is not significant.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125592833","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022724
Krittika Akasarakul, N. Cooharojananone, R. Lipikorn
According to Thailand policy framework which has a policy to expand the market and create opportunities in business by using ICT and E-Commerce for supporting rural community people. However, these communities mostly do not have their own website to sell their products. They have to rely on web portal to sell their local community products. Therefore, having the rural community official website and electronic commerce (E-Commerce) would expect to gain more attention and would be more advantages to the community. Therefore, in this paper, we would like to study factors influencing customer's purchasing intention through internet shopping of One Tambon One Product (OTOP), derived from the concept of One Village One Product (OVOP) in Japan, between on web portal and official web. Several factors such as perceived ease of use, reliability of website, reliability of product and social influences that effect customer's purchasing intention were discussed and analyzed. The data was collected using a simply sampling method with survey participants who are people from each rural area in north eastern of Thailand. Understanding well the factors influencing online purchasing would allow rural people the possibility of making their official OTOP website to finally attract most of their potential consumers and profit most from the opportunities offered by E-Commerce.
{"title":"A study of factors influencing intention to purchase local community product on E-Commerce website: The case of One Tambon One Product (OTOP) in Thailand","authors":"Krittika Akasarakul, N. Cooharojananone, R. Lipikorn","doi":"10.1109/SNPD.2017.8022724","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022724","url":null,"abstract":"According to Thailand policy framework which has a policy to expand the market and create opportunities in business by using ICT and E-Commerce for supporting rural community people. However, these communities mostly do not have their own website to sell their products. They have to rely on web portal to sell their local community products. Therefore, having the rural community official website and electronic commerce (E-Commerce) would expect to gain more attention and would be more advantages to the community. Therefore, in this paper, we would like to study factors influencing customer's purchasing intention through internet shopping of One Tambon One Product (OTOP), derived from the concept of One Village One Product (OVOP) in Japan, between on web portal and official web. Several factors such as perceived ease of use, reliability of website, reliability of product and social influences that effect customer's purchasing intention were discussed and analyzed. The data was collected using a simply sampling method with survey participants who are people from each rural area in north eastern of Thailand. Understanding well the factors influencing online purchasing would allow rural people the possibility of making their official OTOP website to finally attract most of their potential consumers and profit most from the opportunities offered by E-Commerce.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122444877","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022743
Islem Kaabachi, Dorra Jriji, S. Krichen
We investigate in this paper a new variant of multi-depot vehicle routing problem with time windows is studied (GMDVRPTW), an extension of the MDVRPTW. In the new variant, the proposed GMDVRPTW consists of determining the vehicle's speed in order to minimize a function comprising fuel consumption and resulting emission costs. An integer programming model is formulated with two objectives to find the minimum travel cost and total fuel consumption and CO2 emissions under the constrains of time window, capacity of the vehicle, the fleet size. As the problem is an NP-Hard problem, we develop an improved meta-heuristic, based on an ant colony optimization and local search to solve the problem. The results show that the proposed approach is competitive in terms of solution quality.
{"title":"An improved ant colony optimization for green multi-depot vehicle routing problem with time windows","authors":"Islem Kaabachi, Dorra Jriji, S. Krichen","doi":"10.1109/SNPD.2017.8022743","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022743","url":null,"abstract":"We investigate in this paper a new variant of multi-depot vehicle routing problem with time windows is studied (GMDVRPTW), an extension of the MDVRPTW. In the new variant, the proposed GMDVRPTW consists of determining the vehicle's speed in order to minimize a function comprising fuel consumption and resulting emission costs. An integer programming model is formulated with two objectives to find the minimum travel cost and total fuel consumption and CO2 emissions under the constrains of time window, capacity of the vehicle, the fleet size. As the problem is an NP-Hard problem, we develop an improved meta-heuristic, based on an ant colony optimization and local search to solve the problem. The results show that the proposed approach is competitive in terms of solution quality.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129984627","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022651
H. Yoe
Recently, agriculture has developed remarkably. In recent years, the South Korean government has provided a lot of support for smart agriculture. So, South Korean smart farming industry is making a lot of progress lately. Due to the aging population of farmers in the world, governments of developed country are making strenuous efforts to resolve several agricultural problems through smart farming. Farmers also have a lot of interest in smart agriculture, where they can expect to increase their incomes and boost their convenience. In this speech, I want to introduce about the concept of smart farming technology and smart agricultural situation in Korea and following this, I will focus on the status of smart agriculture in major countries, and will attempt to wrap up the lecture by predicting future smart agriculture.
{"title":"Smart farming: ICT based agriculture: Keynote address","authors":"H. Yoe","doi":"10.1109/SNPD.2017.8022651","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022651","url":null,"abstract":"Recently, agriculture has developed remarkably. In recent years, the South Korean government has provided a lot of support for smart agriculture. So, South Korean smart farming industry is making a lot of progress lately. Due to the aging population of farmers in the world, governments of developed country are making strenuous efforts to resolve several agricultural problems through smart farming. Farmers also have a lot of interest in smart agriculture, where they can expect to increase their incomes and boost their convenience. In this speech, I want to introduce about the concept of smart farming technology and smart agricultural situation in Korea and following this, I will focus on the status of smart agriculture in major countries, and will attempt to wrap up the lecture by predicting future smart agriculture.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121837958","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022720
R. Rajagede, Chandra Kusuma Dewa, Afiahayati
Arabic letters have unique characteristics because of similarity of sound produced when reciting few letters. This paper present one of application Convolutional Neural Network (CNN) in speech recognition Arabic letters. CNN has shown very good performance for image and speech recognition int the last few years. This study examined the several types of CNN models as well as compare with some Deep Neural Network (DNN) models to speech datasets used. As a result, CNN with a convolution layer and one layer fully-connected managed to obtain an accuracy of up to 80.75%, far better than the traditional DNN that only able to reach 72.0%.
{"title":"Recognizing Arabic letter utterance using convolutional neural network","authors":"R. Rajagede, Chandra Kusuma Dewa, Afiahayati","doi":"10.1109/SNPD.2017.8022720","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022720","url":null,"abstract":"Arabic letters have unique characteristics because of similarity of sound produced when reciting few letters. This paper present one of application Convolutional Neural Network (CNN) in speech recognition Arabic letters. CNN has shown very good performance for image and speech recognition int the last few years. This study examined the several types of CNN models as well as compare with some Deep Neural Network (DNN) models to speech datasets used. As a result, CNN with a convolution layer and one layer fully-connected managed to obtain an accuracy of up to 80.75%, far better than the traditional DNN that only able to reach 72.0%.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129499554","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022705
N. Lynn, Zin Mar Kyu, Thi Thi Zin, I. Kobayashi
The Body Condition Score (BCS) is the level of energy reserves in many species, including dairy cattle. For the exact management on dairy farms, the judgment process of BCS is critically important. In this study, the implementation of newly developed approach to estimate body condition score is proposed. Back view images of the cow were used in this system. The area around the tailhead and left and right hooks are segmented automatically and then classified that region for estimating the body condition score. The three main steps conducted are (1) segmentation of cows' images, (2) extraction of region of interest (ROI) by using the convex hull method, and (3) calculation of parameter using moving average method. To confirm this new approach, back view images of various cow types are used and the experimental results confirm its effectiveness with accurate results.
{"title":"Estimating body condition score of cows from images with the newly developed approach","authors":"N. Lynn, Zin Mar Kyu, Thi Thi Zin, I. Kobayashi","doi":"10.1109/SNPD.2017.8022705","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022705","url":null,"abstract":"The Body Condition Score (BCS) is the level of energy reserves in many species, including dairy cattle. For the exact management on dairy farms, the judgment process of BCS is critically important. In this study, the implementation of newly developed approach to estimate body condition score is proposed. Back view images of the cow were used in this system. The area around the tailhead and left and right hooks are segmented automatically and then classified that region for estimating the body condition score. The three main steps conducted are (1) segmentation of cows' images, (2) extraction of region of interest (ROI) by using the convex hull method, and (3) calculation of parameter using moving average method. To confirm this new approach, back view images of various cow types are used and the experimental results confirm its effectiveness with accurate results.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124728999","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022701
Koya Kawashima, Wenjun Bai, Changqin Quan
With the number increase of biomedical literatures, biomedical relation extraction discovery from the literature represents a new challenge for researchers in recent years. Then, a system that automatically extracts the related genes to the targeted disease is required. In this paper, we explore text mining and pattern clustering for relation extraction of breast cancer and related genes. It can be considered an unsupervised method and labeled data is not necessary. We firstly extract the candidate genes related to breast cancer by checking the window distance between the appearance of genes and breast cancer in a sentence. Then, two different clustering approaches (simple clustering and K-means clustering) are applied for finding the candidate association words that indicate the relationship between breast cancer and genes. The comparison experiment demonstrates that simple clustering is superior to K-means clustering in this task.
{"title":"Text mining and pattern clustering for relation extraction of breast cancer and related genes","authors":"Koya Kawashima, Wenjun Bai, Changqin Quan","doi":"10.1109/SNPD.2017.8022701","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022701","url":null,"abstract":"With the number increase of biomedical literatures, biomedical relation extraction discovery from the literature represents a new challenge for researchers in recent years. Then, a system that automatically extracts the related genes to the targeted disease is required. In this paper, we explore text mining and pattern clustering for relation extraction of breast cancer and related genes. It can be considered an unsupervised method and labeled data is not necessary. We firstly extract the candidate genes related to breast cancer by checking the window distance between the appearance of genes and breast cancer in a sentence. Then, two different clustering approaches (simple clustering and K-means clustering) are applied for finding the candidate association words that indicate the relationship between breast cancer and genes. The comparison experiment demonstrates that simple clustering is superior to K-means clustering in this task.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125671887","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022698
Yaning Li, Xuelei Wang, Jie Tan, Chengbao Liu, X. Bai
Focus on the first China domestic coking flue gas desulfurization and denitriation integrated device, in order to solve the problem that the entrance parameters fluctuate and a detection lag exists due to the upstream coking workshop, which is extremely unfavorable to the optimal control of desulfurization and denitriation process. An intelligent integrated prediction model of flue gas SO2 concentration, O2 content and NOx concentration was proposed: the mechanism models of SO2, NOx concentration and O2 content were established according to the principle of material balance and reaction kinetics, respectively. For the prediction error, raw data was pretreated and the auxiliary variables were determined by principal component analysis, in order to improve the training speed and generalization ability of neural network, an improved RBFNN combining optimal stopping principle and dual momentum adaptive learning rate was proposed and used to compensate the error. Based on the practical data of two 55-hole and 6-meter top charging coke ovens in the coking group, the effectiveness and superiority of proposed model and method were verified by simulation via comparison of various models.
{"title":"Intelligent integrated coking flue gas indices prediction","authors":"Yaning Li, Xuelei Wang, Jie Tan, Chengbao Liu, X. Bai","doi":"10.1109/SNPD.2017.8022698","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022698","url":null,"abstract":"Focus on the first China domestic coking flue gas desulfurization and denitriation integrated device, in order to solve the problem that the entrance parameters fluctuate and a detection lag exists due to the upstream coking workshop, which is extremely unfavorable to the optimal control of desulfurization and denitriation process. An intelligent integrated prediction model of flue gas SO2 concentration, O2 content and NOx concentration was proposed: the mechanism models of SO2, NOx concentration and O2 content were established according to the principle of material balance and reaction kinetics, respectively. For the prediction error, raw data was pretreated and the auxiliary variables were determined by principal component analysis, in order to improve the training speed and generalization ability of neural network, an improved RBFNN combining optimal stopping principle and dual momentum adaptive learning rate was proposed and used to compensate the error. Based on the practical data of two 55-hole and 6-meter top charging coke ovens in the coking group, the effectiveness and superiority of proposed model and method were verified by simulation via comparison of various models.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116888825","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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