Pub Date : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111552
W. Shangguan, Manqiang Ge
With the rapidly development of economy, traffic congestion has become a bottleneck restricting of the development of the urban economy. As the core of future development and direction of intelligent transportation, the CVIS (Cooperative Vehicle Infrastructure System) is the key to solve the urban traffic congestion problems. And the wireless communication technology of high quality is the key point of research in CVIS. The work of this paper is to build the wireless communication platform of CVIS and research problem of information interaction between DSRC (Dedicated Short Range Communications) and WIFI (Wireless Fidelity) under environment of CVIS. This paper analyzes the application between DSRC and WIFI in CVIS and builds a wireless communication platform based on PCM-9562. Through the study of car-following model with single lane, this paper achieves data exchange between application and communication platform by using GPS information. Combined with MapX, the communication platform completes the real-time display of position, velocity and driving strategy. The result of test shows that double-mode communication platform based on CVIS can realize the real-time transmission of data effectively and assist driver to get the information of position and velocity from itself and other cars and finally provide effective reference information to the driver in the pattern of car-following.
随着经济的快速发展，交通拥堵已成为制约城市经济发展的瓶颈。协同车辆基础设施系统(Cooperative Vehicle Infrastructure System, CVIS)作为未来智能交通发展的核心和方向，是解决城市交通拥堵问题的关键。而高质量的无线通信技术是CVIS研究的重点。本文的工作是搭建CVIS无线通信平台，研究CVIS环境下DSRC (Dedicated Short Range Communications)与WIFI (wireless Fidelity)之间的信息交互问题。本文分析了DSRC与WIFI在CVIS中的应用，搭建了一个基于PCM-9562的无线通信平台。本文通过对单车道车辆跟随模型的研究，利用GPS信息实现了应用程序与通信平台之间的数据交换。通信平台结合MapX完成位置、速度和行驶策略的实时显示。测试结果表明，基于CVIS的双模通信平台可以有效地实现数据的实时传输，辅助驾驶员获取自身和其他车辆的位置和速度信息，最终为驾驶员在跟车模式下提供有效的参考信息。
{"title":"Design and realization of double-mode communication platform based on CVIS","authors":"W. Shangguan, Manqiang Ge","doi":"10.1109/ICAIOT.2015.7111552","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111552","url":null,"abstract":"With the rapidly development of economy, traffic congestion has become a bottleneck restricting of the development of the urban economy. As the core of future development and direction of intelligent transportation, the CVIS (Cooperative Vehicle Infrastructure System) is the key to solve the urban traffic congestion problems. And the wireless communication technology of high quality is the key point of research in CVIS. The work of this paper is to build the wireless communication platform of CVIS and research problem of information interaction between DSRC (Dedicated Short Range Communications) and WIFI (Wireless Fidelity) under environment of CVIS. This paper analyzes the application between DSRC and WIFI in CVIS and builds a wireless communication platform based on PCM-9562. Through the study of car-following model with single lane, this paper achieves data exchange between application and communication platform by using GPS information. Combined with MapX, the communication platform completes the real-time display of position, velocity and driving strategy. The result of test shows that double-mode communication platform based on CVIS can realize the real-time transmission of data effectively and assist driver to get the information of position and velocity from itself and other cars and finally provide effective reference information to the driver in the pattern of car-following.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128108256","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111526
Vincent Qi Chen, K. Yuen
Products have similarities which can be analyzed to recommend products to consumers with different preferences. This paper combines Primitive Cognitive Network Process (PCNP) and Self-Organizing Map (SOM) to cluster products into appropriate categories on the basis of consumer preferences and product similarities. PCNP is an ideal alternative of Analytic Hierarchy Process (AHP) to quantify the weights for the attributes used in SOM. To demonstrate the applicability of PCNP-SOM, an example of computer product recommendation is illustrated.
{"title":"Towards a hybrid approach of Primitive Cognitive Network Process and Self-Organizing Map for computer product recommendation","authors":"Vincent Qi Chen, K. Yuen","doi":"10.1109/ICAIOT.2015.7111526","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111526","url":null,"abstract":"Products have similarities which can be analyzed to recommend products to consumers with different preferences. This paper combines Primitive Cognitive Network Process (PCNP) and Self-Organizing Map (SOM) to cluster products into appropriate categories on the basis of consumer preferences and product similarities. PCNP is an ideal alternative of Analytic Hierarchy Process (AHP) to quantify the weights for the attributes used in SOM. To demonstrate the applicability of PCNP-SOM, an example of computer product recommendation is illustrated.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"2012 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131765849","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111539
Zhaoguang Liu, Xing Zhang, Yang-Yang, Cengceng Wu
Computer vision-based fire detection involves flame detection and smoke detection. This paper proposes a new flame detection algorithm, which is based on a Bag-of-Features technique in the YUV color space. Inspired by that the color of flame in image and video will fall in certain regions in the color space, models of flame pixels and non-flame pixels are established based on code book in the training phase in our proposal. In the testing phase, the input image is split into some N×N blocks and each block is classified respectively. In each N×N block, the pixels values in the YUV color space are extracted as features, just as in the training phase. According to the experimental results, our proposed method can reduce the number of false alarms greatly compared with an alternative algorithm, while it also ensures the accurate classification of positive samples. The classification performance of our proposed method is better than that of alternative algorithms.
{"title":"A flame detection algorithm based on Bag-of-Features in the YUV color space","authors":"Zhaoguang Liu, Xing Zhang, Yang-Yang, Cengceng Wu","doi":"10.1109/ICAIOT.2015.7111539","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111539","url":null,"abstract":"Computer vision-based fire detection involves flame detection and smoke detection. This paper proposes a new flame detection algorithm, which is based on a Bag-of-Features technique in the YUV color space. Inspired by that the color of flame in image and video will fall in certain regions in the color space, models of flame pixels and non-flame pixels are established based on code book in the training phase in our proposal. In the testing phase, the input image is split into some N×N blocks and each block is classified respectively. In each N×N block, the pixels values in the YUV color space are extracted as features, just as in the training phase. According to the experimental results, our proposed method can reduce the number of false alarms greatly compared with an alternative algorithm, while it also ensures the accurate classification of positive samples. The classification performance of our proposed method is better than that of alternative algorithms.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130593842","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111543
Du Xiping, Liu Jiafeng, Tang Xianglong
Recently, sparse representation has been used in visual tracking, and related trackers have emerged. However, such sparse representation is not stable and has the potential to represent a candidate with dissimilar target templates. Therefore, a new tracker based weighted sparse representation (WSRT) is proposed. Specifically, to represent a candidate, each target template is weighted according to its similarity to the candidate. The bigger the similarity is, the bigger the probability of the target template to be chosen will be. The proposed tracker chooses the similar target templates to represent each candidate and reflects the locality structure between the candidate and target templates. Experimental results show that the proposed tracker has excellent performance.
{"title":"Visual tracking via weighted sparse representation","authors":"Du Xiping, Liu Jiafeng, Tang Xianglong","doi":"10.1109/ICAIOT.2015.7111543","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111543","url":null,"abstract":"Recently, sparse representation has been used in visual tracking, and related trackers have emerged. However, such sparse representation is not stable and has the potential to represent a candidate with dissimilar target templates. Therefore, a new tracker based weighted sparse representation (WSRT) is proposed. Specifically, to represent a candidate, each target template is weighted according to its similarity to the candidate. The bigger the similarity is, the bigger the probability of the target template to be chosen will be. The proposed tracker chooses the similar target templates to represent each candidate and reflects the locality structure between the candidate and target templates. Experimental results show that the proposed tracker has excellent performance.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115596909","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111532
Fu Liu, Huiying Liu, Lei Gao
Hand shape recognition method based on geometric features uses individual information limitedly and inadequately. To solve this problem, this paper proposes a hand shape recognition method based on contour features of fingers. Firstly, we separate the four fingers and use curve fitting method to position the axis of finger. Then the matched fingers are normalized by translation and rotational alignment, so we can conduct the matching of contour features. Finally, in order to further improve the recognition rate, particle swarm optimization (PSO for short) is used to optimize the cut-off coefficient and the weight values of different fingers. Experimental results show that the proposed method can locate hand more accurately and make full use of hand information. It can also avoid the influence of inaccurate feature points locating and unstable contour around finger valleys. The recognition rate can reach 94.78%.
{"title":"Hand recognition based on finger-contour and PSO","authors":"Fu Liu, Huiying Liu, Lei Gao","doi":"10.1109/ICAIOT.2015.7111532","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111532","url":null,"abstract":"Hand shape recognition method based on geometric features uses individual information limitedly and inadequately. To solve this problem, this paper proposes a hand shape recognition method based on contour features of fingers. Firstly, we separate the four fingers and use curve fitting method to position the axis of finger. Then the matched fingers are normalized by translation and rotational alignment, so we can conduct the matching of contour features. Finally, in order to further improve the recognition rate, particle swarm optimization (PSO for short) is used to optimize the cut-off coefficient and the weight values of different fingers. Experimental results show that the proposed method can locate hand more accurately and make full use of hand information. It can also avoid the influence of inaccurate feature points locating and unstable contour around finger valleys. The recognition rate can reach 94.78%.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124974782","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111525
Ruikun Ma, Zhi Li, Junyan Tan
This paper presents a new version of support vector machine (SVM) named density induced p-norm SVM (0 <; p <; 1), DPSVM for shot. Our DPSVM introduces the density degrees into the standard p-norm SVM. It extracts the relative density degrees for the training examples and takes these degrees as relative margins for corresponding training examples. Our DPSVM not only inherits good performance of p-norm SVM which can realize feature selection and classification simultaneously, but also improves the performance of p-norm SVM. The numerical experiments results show that our DPSVM is more effective than some usual methods in feature selection and classification.
{"title":"Density induced p-norm support vector machine for binary classification","authors":"Ruikun Ma, Zhi Li, Junyan Tan","doi":"10.1109/ICAIOT.2015.7111525","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111525","url":null,"abstract":"This paper presents a new version of support vector machine (SVM) named density induced p-norm SVM (0 <; p <; 1), DPSVM for shot. Our DPSVM introduces the density degrees into the standard p-norm SVM. It extracts the relative density degrees for the training examples and takes these degrees as relative margins for corresponding training examples. Our DPSVM not only inherits good performance of p-norm SVM which can realize feature selection and classification simultaneously, but also improves the performance of p-norm SVM. The numerical experiments results show that our DPSVM is more effective than some usual methods in feature selection and classification.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121525462","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111556
Guosheng Zhao, N. Zhang, L. Sheng
This paper proposed a cognitive model for Ad hoc network, and combined formal modeling of cognitive model with quantitative analysis of cognitive performance, thus at the same time of formal modeling through quantitative analysis obtained Ad hoc network cognitive performance parameters.
{"title":"Study of cognitive model for Ad hoc network based on high-order multi-type π calculus modeling","authors":"Guosheng Zhao, N. Zhang, L. Sheng","doi":"10.1109/ICAIOT.2015.7111556","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111556","url":null,"abstract":"This paper proposed a cognitive model for Ad hoc network, and combined formal modeling of cognitive model with quantitative analysis of cognitive performance, thus at the same time of formal modeling through quantitative analysis obtained Ad hoc network cognitive performance parameters.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126138306","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111550
D. Arias, G. Rodriguez
This paper studies the Okumura- Hat propagation model on CDMA technology applied in AMI (Advanced Metering Infrastructure). The aim of this proposal is to get information from the intelligent meter such us: outage management system, status and ratings reading. Prepaid services are oriented to the specific characteristics of rural dwellers. Furthermore, it allows to the energy distribution companies to know the energy consumption in real time. The Okumura - Hata propagation model helps to evaluate a communication system due to its good practices and results obtained with this method using cellular technology. The use of CDMA technology in electrical measurement systems helps to reduce the costs of non-technical losses, resulting in: better quality in the electrical systems and obtaining actual data readings that improves communication between the consumer and the distributor.
{"title":"Performance of Advanced Metering Infrastructure using cellular communication based on uplink CDMA","authors":"D. Arias, G. Rodriguez","doi":"10.1109/ICAIOT.2015.7111550","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111550","url":null,"abstract":"This paper studies the Okumura- Hat propagation model on CDMA technology applied in AMI (Advanced Metering Infrastructure). The aim of this proposal is to get information from the intelligent meter such us: outage management system, status and ratings reading. Prepaid services are oriented to the specific characteristics of rural dwellers. Furthermore, it allows to the energy distribution companies to know the energy consumption in real time. The Okumura - Hata propagation model helps to evaluate a communication system due to its good practices and results obtained with this method using cellular technology. The use of CDMA technology in electrical measurement systems helps to reduce the costs of non-technical losses, resulting in: better quality in the electrical systems and obtaining actual data readings that improves communication between the consumer and the distributor.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132707851","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111531
Zhang Long, Zhao Yunxue, Zhang Peng, Yan Ke, Zhang Wei
Accent is a critical important component of spoken communication, which plays a very important role in spoken communication. In this paper, we conduct accent by using RASTA - PLP algorithm to extract short-time spectrum features of each speech segment based on sub-segment splicing information. We build short-time spectrum feature sets based on RASTA - PLP algorithm. And we choose NaiveBayes classifier to model the feature sets. NaiveBayes is to choose the class with maximum posteriori probability as the object's class. This classification method makes full use of the related phonetic features of speech segment. Based on short-time spectrum of RASTA - PLP feature sets respectively achieve 80.8% accent detection accuracy on ASCCD and on ASCCD (NOISEX92-white). The experimental results indicate that based on sub-segment splicing feature structured method of RASTA - PLP can be used in Chinese accent detection study. RASTA-PLP algorithm is robust on ASSCD and on ASSCD (NOISEX92-white).
{"title":"Chinese accent detection research based on RASTA - PLP algorithm","authors":"Zhang Long, Zhao Yunxue, Zhang Peng, Yan Ke, Zhang Wei","doi":"10.1109/ICAIOT.2015.7111531","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111531","url":null,"abstract":"Accent is a critical important component of spoken communication, which plays a very important role in spoken communication. In this paper, we conduct accent by using RASTA - PLP algorithm to extract short-time spectrum features of each speech segment based on sub-segment splicing information. We build short-time spectrum feature sets based on RASTA - PLP algorithm. And we choose NaiveBayes classifier to model the feature sets. NaiveBayes is to choose the class with maximum posteriori probability as the object's class. This classification method makes full use of the related phonetic features of speech segment. Based on short-time spectrum of RASTA - PLP feature sets respectively achieve 80.8% accent detection accuracy on ASCCD and on ASCCD (NOISEX92-white). The experimental results indicate that based on sub-segment splicing feature structured method of RASTA - PLP can be used in Chinese accent detection study. RASTA-PLP algorithm is robust on ASSCD and on ASSCD (NOISEX92-white).","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122712329","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 : 2015-05-25DOI: 10.1109/ICAIOT.2015.7111557
Liu Xintian, Zeng Guojian, He Yao, Dong Bo, Xu Xingwu
Temperature has a direct impact on the capacity fading of a power Li-ion battery during the battery's lifecycle; however, the inner temperature of the battery cannot be measured directly because of the sealed structure. To address this problem, we estimate the inner temperature of a Li-ion battery by measuring the surface and ambient temperature using an equivalent thermal model to build the ETM-Arrhenius (equivalent thermal model-Arrhenius) model that models the dependence of the battery capacity fading on the inner temperature to enable the accurate prediction of the capacity fading characteristics of a Li-ion battery during its lifecycle. We conducted a lifecycle test on a Li-ion battery at different temperatures, and the results indicate that the ETM-Arrhenius model can predict the capacity fading characteristics of a Li-ion battery accurately during its lifecycle; in addition, when the model is used in EFK, UKF and other common state-of-charge (SOC) estimation algorithms, the accuracy of the SOC estimation can be improved significantly.
{"title":"Research on the capacity fading characteristics of a Li-ion battery based on an equivalent thermal model","authors":"Liu Xintian, Zeng Guojian, He Yao, Dong Bo, Xu Xingwu","doi":"10.1109/ICAIOT.2015.7111557","DOIUrl":"https://doi.org/10.1109/ICAIOT.2015.7111557","url":null,"abstract":"Temperature has a direct impact on the capacity fading of a power Li-ion battery during the battery's lifecycle; however, the inner temperature of the battery cannot be measured directly because of the sealed structure. To address this problem, we estimate the inner temperature of a Li-ion battery by measuring the surface and ambient temperature using an equivalent thermal model to build the ETM-Arrhenius (equivalent thermal model-Arrhenius) model that models the dependence of the battery capacity fading on the inner temperature to enable the accurate prediction of the capacity fading characteristics of a Li-ion battery during its lifecycle. We conducted a lifecycle test on a Li-ion battery at different temperatures, and the results indicate that the ETM-Arrhenius model can predict the capacity fading characteristics of a Li-ion battery accurately during its lifecycle; in addition, when the model is used in EFK, UKF and other common state-of-charge (SOC) estimation algorithms, the accuracy of the SOC estimation can be improved significantly.","PeriodicalId":310429,"journal":{"name":"Proceedings of 2015 International Conference on Intelligent Computing and Internet of Things","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121839300","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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