Modeling of nonlinear system based on deep learning framework

Xiangjun, Jin; Shao, Jie; Zhang, Xin; An, Wenwei; Malekian, Reza

doi:10.1007/s11071-015-2571-6

Cited by 91 publications

(45 citation statements)

References 16 publications

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“…These are much higher than the reasonable range of 6.0-7.0. Once housing prices decrease, local governments would face a serious debt crisis from declining land values, properties developed by real estate enterprises would be unsellable, individuals would bear enormous losses [47,48], and banks could not recover their loans, which might finally cause financial and even economic crisis. The outcome of developments in Japan in the 1980s is a valuable lesson.…”

Section: Discussionmentioning

confidence: 99%

A Vector Auto Regression Model Applied to Real Estate Development Investment: A Statistic Analysis

et al. 2016

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This study analyzes the economic system dynamics of investment in real estate from mainly four participants in China. Local governments limit the supply of commercial and residential land to raise fiscal revenue, and expand debts by land mortgage to develop industrial zones and parks. Led by local government, banks and real estate development enterprises forge a coalition on real estate investment and facilitate real estate price appreciation. The above theoretical model is empirically evidenced with VAR (Vector Auto Regression) methodology. A panel VAR model shows that land leasing and real estate price appreciation positively affect local government general fiscal revenue. Additional VAR models find that bank credit in addition to private and foreign funds respectively have strong positive dynamic effects on housing prices. Housing prices also have a strong positive impact on speculation from private funds and hot money.

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Section: Discussionmentioning

confidence: 99%

A Vector Auto Regression Model Applied to Real Estate Development Investment: A Statistic Analysis

et al. 2016

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“…The data of these communication styles is similar but not compatible because of the lack of unified interaction interfaces. (2) Due to the lack of service contents [80,81] and service styles, the information is transferred from the ship terminal to the coast station only to meet the requirement of the administration. A general service platform should be established to provide various information services.…”

Section: The Limit Of Transmission For the Waterway Traffic Informationmentioning

confidence: 99%

The Development of Key Technologies in Applications of Vessels Connected to the Internet

Tian

Liu

et al. 2017

Symmetry

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Abstract:With the development of science and technology, traffic perception, communication, information processing, artificial intelligence and the shipping information system have become important in supporting the realization of intelligent shipping transportation. Against this background, the Internet of Vessels (IoV) is proposed to integrate all these advanced technologies into a platform to meet the requirements of international and regional transportations. The purpose of this paper is to analyze how to benefit from the Internet of Vessels to improve the efficiency and safety of shipping, and promote the development of world transportation. In this paper, the IoV is introduced and its main architectures are outlined. Furthermore, the characteristics of the Internet of Vessels are described. Several important applications that illustrate the interaction of the Internet of Vessels' components are proposed. Due to the development of the Internet of Vessels still being in its primary stage, challenges and prospects are identified and addressed. Finally, the main conclusions are drawn and future research priorities are provided for reference and as professional suggestions for future researchers in this field.

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“…On the contrary, in the later stage of the search, c 1 takes a smaller value, while c 2 takes a larger value, which can make the particles learn more from the social optimal solutions and learn less from their own optimal solutions, and is conducive to quickly converge to the global optimal solution. In addition, in the reference literature [32][33][34], the relative nonlinear adjustment pairing experiments were carried out, and it was found that when the sum of c 1 and c 2 is less than 3, the algorithm performance is the best. Therefore, the learning factor of asynchronous change strategy is adopted in this study, as shown in Equations (9) and (10).…”

Section: Location Prediction Model Based On Pso-fnnmentioning

confidence: 99%

An Improved Particle Swarm Optimization-Based Feed-Forward Neural Network Combined with RFID Sensors to Indoor Localization

Wang

Shi

2017

Information

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Location-based services (LBS) have long been recognized as a significant component of the emerging information services. However, the localization cost and the performance of algorithm still need to be optimized. In the study, an improved particle swarm optimization algorithm based on a feed-forward neural network (IMPSO-FNN) combined with RFID sensors is proposed, which can achieve the best indoor positioning location and overcome the problems effectively. In IMPSO-FNN, an improved PSO algorithm (IMPSO) is developed to determine the optimal connecting weights and markedly optimize the network parameters and structural parameters for the FNN, and then an optimal location prediction model is established by the IMPSO-FNN. To avoid the interference of environmental noise for the experimental data, some preprocessing methods are used during the positioning process. The computational results for learning two continuous functions show that the proposed positioning algorithm has a faster convergence rate and higher generalization performance. The model evaluation results also verify that the proposed positioning method really is superior to other algorithms in terms of the learning ability, efficiency, and positioning accuracy.

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Modeling of nonlinear system based on deep learning framework

Cited by 91 publications

References 16 publications

A Vector Auto Regression Model Applied to Real Estate Development Investment: A Statistic Analysis

A Vector Auto Regression Model Applied to Real Estate Development Investment: A Statistic Analysis

The Development of Key Technologies in Applications of Vessels Connected to the Internet

An Improved Particle Swarm Optimization-Based Feed-Forward Neural Network Combined with RFID Sensors to Indoor Localization

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