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Open Access
Article
Publication date: 31 August 2011

Joonhyuk Song

This paper estimates a Nelson-Siegel model under the state-space representation in order to circumvent the shortcomings of the conventional Nelson-Siegel model and evaluates the…

26

Abstract

This paper estimates a Nelson-Siegel model under the state-space representation in order to circumvent the shortcomings of the conventional Nelson-Siegel model and evaluates the predictive ability of the estimated model. The results indicate that the estimated Nelson-Siegel time-varying three factors have close relations to their counterparts : level, slope and curvature and the inflection of the Korean yield curve is located around the maturity of 55-month. Meanwhile, each factor is found to have unit-root but differenced-factors do not show signs of unit-roots, hence proved I (1) series. In order to assess the efficacy of the estimated model, we compare the yield prediction from our model with several natural competitors : random walk, Fama-Bliss, and Cochrane-Piazzesi. With respect to out-of-sample performance, Fama-Bliss model proves to be the worst in term structure forecasts in Korea. The predictive performance differs between the random walk and the state-space Nelson-Siegel model depending on the forecast horizon lengths. At the shorter horizon, the state-space Nelson-Siegel model outperforms the random walk, but the table is turned in the longer horizon

Details

Journal of Derivatives and Quantitative Studies, vol. 19 no. 3
Type: Research Article
ISSN: 2713-6647

Keywords

Open Access
Article
Publication date: 7 April 2015

Yujun Cao, Xin Li, Zhixiong Zhang and Jianzhong Shang

This paper aims to clarify the predicting and compensating method of aeroplane assembly. It proposes modeling the process of assembly. The paper aims to solve the precision…

1438

Abstract

Purpose

This paper aims to clarify the predicting and compensating method of aeroplane assembly. It proposes modeling the process of assembly. The paper aims to solve the precision assembly of aeroplane, which includes predicting the assembly variation and compensating the assembly errors.

Design/methodology/approach

The paper opted for an exploratory study using the state space theory and small displacement torsor theory. The assembly variation propagation model is established. The experiment data are obtained by a real small aeroplane assembly process.

Findings

The paper provides the predicting and compensating method for aeroplane assembly accuracy.

Originality/value

This paper fulfils an identified need to study how the assembly variation propagates in the assembly process.

Details

Assembly Automation, vol. 35 no. 2
Type: Research Article
ISSN: 0144-5154

Keywords

Open Access
Article
Publication date: 13 September 2022

Haitao Ding, Wei Li, Nan Xu and Jianwei Zhang

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected…

Abstract

Purpose

This study aims to propose an enhanced eco-driving strategy based on reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the connected environment.

Design/methodology/approach

In this paper, an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed for connected EVs. The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving. Moreover, this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.

Findings

To illustrate the performance for the EEDC-HRL, the controlled EV was trained and tested in various traffic flow states. The experimental results demonstrate that the proposed technique can effectively improve energy efficiency, without sacrificing travel efficiency, comfort, safety and lane-changing performance in different traffic flow states.

Originality/value

In light of the aforementioned discussion, the contributions of this paper are two-fold. An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space (EEDC-HRL) is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs. A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

Details

Journal of Intelligent and Connected Vehicles, vol. 5 no. 3
Type: Research Article
ISSN: 2399-9802

Keywords

Content available
Book part
Publication date: 16 September 2022

Pedro Brinca, Nikolay Iskrev and Francesca Loria

Since its introduction by Chari, Kehoe, and McGrattan (2007), Business Cycle Accounting (BCA) exercises have become widespread. Much attention has been devoted to the results of

Abstract

Since its introduction by Chari, Kehoe, and McGrattan (2007), Business Cycle Accounting (BCA) exercises have become widespread. Much attention has been devoted to the results of such exercises and to methodological departures from the baseline methodology. Little attention has been paid to identification issues within these classes of models. In this chapter, the authors investigate whether such issues are of concern in the original methodology and in an extension proposed by Šustek (2011) called Monetary Business Cycle Accounting. The authors resort to two types of identification tests in population. One concerns strict identification as theorized by Komunjer and Ng (2011) while the other deals both with strict and weak identification as in Iskrev (2010). Most importantly, the authors explore the extent to which these weak identification problems affect the main economic takeaways and find that the identification deficiencies are not relevant for the standard BCA model. Finally, the authors compute some statistics of interest to practitioners of the BCA methodology.

Details

Essays in Honour of Fabio Canova
Type: Book
ISBN: 978-1-80382-636-3

Keywords

Open Access
Article
Publication date: 31 March 2023

Yong Chen, Zhixian Zhan and Wei Zhang

As the strategy of 5G new infrastructure is deployed and advanced, 5G-R becomes the primary technical system for future mobile communication of China’s railway. V2V communication…

Abstract

Purpose

As the strategy of 5G new infrastructure is deployed and advanced, 5G-R becomes the primary technical system for future mobile communication of China’s railway. V2V communication is also an important application scenario of 5G communication systems on high-speed railways, so time synchronization between vehicles is critical for train control systems to be real-time and safe. How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.

Design/methodology/approach

This paper proposed a time synchronization method based on model predictive control (MPC) for V2V communication. Firstly, a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway (5G-R) system. Secondly, an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles. Finally, the optimal clock offset was solved through multistep prediction, rolling optimization and other control methods, and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.

Findings

The results of simulation tests conducted with and without a repeater, respectively, show that the proposed method can realize time synchronization of V2V communication in both scenarios. Compared with other methods, the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.

Originality/value

This paper proposed an MPC-based time synchronization method for V2V communication under 5G-R. Through the construction of MPC controllers for clocks of adjacent vehicles, time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction, rolling optimization, and feedback correction. In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods, the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss, which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication. The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.

Details

Railway Sciences, vol. 2 no. 1
Type: Research Article
ISSN: 2755-0907

Keywords

Open Access
Article
Publication date: 18 October 2018

Yang Guan, Shengbo Eben Li, Jingliang Duan, Wenjun Wang and Bo Cheng

Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model

6383

Abstract

Purpose

Decision-making is one of the key technologies for self-driving cars. The high dependency of previously existing methods on human driving data or rules makes it difficult to model policies for different driving situations.

Design/methodology/approach

In this research, a probabilistic decision-making method based on the Markov decision process (MDP) is proposed to deduce the optimal maneuver automatically in a two-lane highway scenario without using any human data. The decision-making issues in a traffic environment are formulated as the MDP by defining basic elements including states, actions and basic models. Transition and reward models are defined by using a complete prediction model of the surrounding cars. An optimal policy was deduced using a dynamic programing method and evaluated under a two-dimensional simulation environment.

Findings

Results show that, at the given scenario, the self-driving car maintained safety and efficiency with the proposed policy.

Originality/value

This paper presents a framework used to derive a driving policy for self-driving cars without relying on any human driving data or rules modeled by hand.

Details

Journal of Intelligent and Connected Vehicles, vol. 1 no. 2
Type: Research Article
ISSN: 2399-9802

Keywords

Open Access
Article
Publication date: 3 December 2020

Peiqing Li, Huile Wang, Zixiao Xing, Kanglong Ye and Qipeng Li

The operation state of lithium-ion battery for vehicle is unknown and the remaining life is uncertain. In order to improve the performance of battery state prediction, in this…

1703

Abstract

Purpose

The operation state of lithium-ion battery for vehicle is unknown and the remaining life is uncertain. In order to improve the performance of battery state prediction, in this paper, a joint estimation method of state of charge (SOC) and state of health (SOH) for lithium-ion batteries based on multi-scale theory is designed.

Design/methodology/approach

In this paper, a joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is designed. The venin equivalent circuit model and fast static calibration method are used to fit the relationship between open-circuit voltage and SOC, and the resistance and capacitance parameters in the model are identified based on exponential fitting method. A battery capacity model for SOH estimation is established. A multi-time scale EKF filtering algorithm is used to estimate the SOC and SOH of lithium-ion batteries.

Findings

The SOC and SOH changes in dynamic operation of lithium-ion batteries are accurately predicted so that batteries can be recycled more effectively in the whole vehicle process.

Originality/value

A joint estimation method of SOC and SOH for lithium-ion batteries based on multi-scale theory is accurately predicted and can be recycled more effectively in the whole vehicle process.

Details

Journal of Intelligent Manufacturing and Special Equipment, vol. 1 no. 1
Type: Research Article
ISSN: 2633-6596

Keywords

Open Access
Article
Publication date: 28 February 2019

Aymen Ben Rejeb and Mongi Arfaoui

The purpose of this paper is to investigate whether Islamic stock indexes outperform conventional stock indexes, in terms of informational efficiency and risk, during the recent…

5005

Abstract

Purpose

The purpose of this paper is to investigate whether Islamic stock indexes outperform conventional stock indexes, in terms of informational efficiency and risk, during the recent financial instability period.

Design/methodology/approach

The paper uses a state space model combined with a standard GARCH(1,1) specification while taking into account structural breakpoints. The authors allow for efficiency and volatility spillovers to be time-varying and consider break dates to locate periods of financial instability.

Findings

Empirical results show that Islamic stock indexes are more volatile than their conventional counterparts and are not totally immune to the global financial crisis. As regards of the informational efficiency, the results show that the Islamic stock indexes are more efficient than the conventional stock indexes.

Practical implications

Resulting evidence of this paper has several implications for international investors who wish to invest in Islamic and/or conventional stock markets. Policy makers and even academics and Sharias researchers should as well take preventive measures in order to ensure the stability of Islamic stock markets during turmoil periods. Overall, prudent risk management and precocious financial practices are relevant and crucial for both Islamic and conventional financial markets.

Originality/value

The originality of this study is performed by the use of time-varying models for volatility spillovers and informational efficiency. It considers structural break dates that think about the dynamic effect of informational flows on stock markets. The study was developed in a global framework using international data. The global analysis allows avoiding country specific effects.

Details

European Journal of Management and Business Economics, vol. 28 no. 3
Type: Research Article
ISSN: 2444-8494

Keywords

Open Access
Article
Publication date: 19 March 2021

Vicente Ramos, Woraphon Yamaka, Bartomeu Alorda and Songsak Sriboonchitta

This paper aims to illustrate the potential of high-frequency data for tourism and hospitality analysis, through two research objectives: First, this study describes and test a…

1827

Abstract

Purpose

This paper aims to illustrate the potential of high-frequency data for tourism and hospitality analysis, through two research objectives: First, this study describes and test a novel high-frequency forecasting methodology applied on big data characterized by fine-grained time and spatial resolution; Second, this paper elaborates on those estimates’ usefulness for visitors and tourism public and private stakeholders, whose decisions are increasingly focusing on short-time horizons.

Design/methodology/approach

This study uses the technical communications between mobile devices and WiFi networks to build a high frequency and precise geolocation of big data. The empirical section compares the forecasting accuracy of several artificial intelligence and time series models.

Findings

The results robustly indicate the long short-term memory networks model superiority, both for in-sample and out-of-sample forecasting. Hence, the proposed methodology provides estimates which are remarkably better than making short-time decision considering the current number of residents and visitors (Naïve I model).

Practical implications

A discussion section exemplifies how high-frequency forecasts can be incorporated into tourism information and management tools to improve visitors’ experience and tourism stakeholders’ decision-making. Particularly, the paper details its applicability to managing overtourism and Covid-19 mitigating measures.

Originality/value

High-frequency forecast is new in tourism studies and the discussion sheds light on the relevance of this time horizon for dealing with some current tourism challenges. For many tourism-related issues, what to do next is not anymore what to do tomorrow or the next week.

Plain Language Summary

This research initiates high-frequency forecasting in tourism and hospitality studies. Additionally, we detail several examples of how anticipating urban crowdedness requires high-frequency data and can improve visitors’ experience and public and private decision-making.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 6
Type: Research Article
ISSN: 0959-6119

Keywords

Open Access
Article
Publication date: 19 September 2019

Mario Schenk, Annette Muetze, Klaus Krischan and Christian Magele

The purpose of this paper is to evaluate the worst-case behavior of a given electronic circuit by varying the values of the components in a meaningful way in order not to exceed…

1794

Abstract

Purpose

The purpose of this paper is to evaluate the worst-case behavior of a given electronic circuit by varying the values of the components in a meaningful way in order not to exceed pre-defined currents or voltages limits during a transient operation.

Design/methodology/approach

An analytic formulation is used to identify the time-dependent solution of voltages or currents using proper state equations in closed form. Circuits with linear elements can be described by a system of differential equations, while circuits composing nonlinear elements are described by piecewise-linear models. A sequential quadratic program (SQP) is used to find the worst-case scenario.

Findings

It is found that the worst-case scenario can be obtained with as few solutions to the forward problem as possible by applying an SQP method.

Originality/value

The SQP method in combination with the analytic forward solver approach shows that the worst-case limit converges in a few steps even if the worst-case limit is not on the boundary of the parameters.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering , vol. 38 no. 5
Type: Research Article
ISSN: 0332-1649

Keywords

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