Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the...Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the model using the reference data set collected from the healthy structure and employing the trained model to identify outlier conditions representing the damaged state.In this paper,the coefficients and the residuals of the autoregressive model with exogenous input created using only the measured output signals are extracted as damage features.These features obtained at the baseline state for each sensor cluster are then utilized to train the one class support vector machine,an unsupervised classifier generating a decision function using only patterns belonging to this baseline state.Structural damage,once detected by the trained machine,a damage index based on comparison of the residuals between the trained class and the outlier state is implemented for localizing damage.The two-step damage assessment framework is first implemented on an eight degree-of-freedom numerical model with the effects of measurement noise integrated.Subsequently,vibration data collected from a one-story one-bay reinforced concrete frame inflicted with progressive levels of damage have been utilized to verify the accuracy and robustness of the proposed methodology.展开更多
Based on the commodity property and finance property of gold in the international gold futures market,the influence factors of international gold futures price volatility are analyzed from the perspectives of supply a...Based on the commodity property and finance property of gold in the international gold futures market,the influence factors of international gold futures price volatility are analyzed from the perspectives of supply and demand factors,financial factors and speculation factors.The structural vector autoregression(SVAR)model is applied to investigating the direction and strength of the effects of influence factors on the international gold futures prices and the variance decomposition approach(VDA)is used to compare the contributions of these factors.The results show that the supply and demand factors still play a fundamental role in the international gold futures price volatility and the role of“China’s gold demand”is exaggerated.The financial factors and speculation factors have significant impacts on the international gold futures price volatility,which reflects that the financial property of gold becomes increasingly important.Governments and investors should pay close attention to the financial property of gold futures.展开更多
Empirical research has shown that there were international spillover effects from the U.S. monetary policy to output level, net exports and price levels of each country, and the impact on prices in each country was of...Empirical research has shown that there were international spillover effects from the U.S. monetary policy to output level, net exports and price levels of each country, and the impact on prices in each country was of synchronous effect. The structural impulse response analysis showed that U.S. monetary policy could improve U.S. income and payment without damaging U.S. economic growth, but the shocks negatively affected the economic growth in the rest of the world. Hence, it's important to pay close attention to the moral risks of U.S. monetary policy to evade the global shocks caused by the "benefit-itself-at-the-expense-of-others" polices of the American government. Besides these findings, U.S. monetary policy shocks strongly affect China's trade surplus fluctuations. Based on this, we propose that the approaches of balancing China's current account could be explored efficiently from the perspective of monetary policy.展开更多
The paper aims to analyze the monetary transmission model between the monetary policy and the labor market variable of unemployment.The results of the data show that,the external shocks have an important impact especi...The paper aims to analyze the monetary transmission model between the monetary policy and the labor market variable of unemployment.The results of the data show that,the external shocks have an important impact especially on the Romanian interest rates but also on the domestic production;however,the impact is not significant on unemployment,which proves the resilience of the domestic labor market.The central bank policy rate has a stabilizing effect on the unemployment rate in case of an increase in the euro area policy rate.展开更多
基金funding provided by the Scientific and Technological Research Council of Türkiye(TÜBİTAK).
文摘Machine learning algorithms operating in an unsupervised fashion has emerged as promising tools for detecting structural damage in an automated fashion.Its essence relies on selecting appropriate features to train the model using the reference data set collected from the healthy structure and employing the trained model to identify outlier conditions representing the damaged state.In this paper,the coefficients and the residuals of the autoregressive model with exogenous input created using only the measured output signals are extracted as damage features.These features obtained at the baseline state for each sensor cluster are then utilized to train the one class support vector machine,an unsupervised classifier generating a decision function using only patterns belonging to this baseline state.Structural damage,once detected by the trained machine,a damage index based on comparison of the residuals between the trained class and the outlier state is implemented for localizing damage.The two-step damage assessment framework is first implemented on an eight degree-of-freedom numerical model with the effects of measurement noise integrated.Subsequently,vibration data collected from a one-story one-bay reinforced concrete frame inflicted with progressive levels of damage have been utilized to verify the accuracy and robustness of the proposed methodology.
基金Projects(71874210,71633006,71501193) supported by the National Natural Science Foundation of China
文摘Based on the commodity property and finance property of gold in the international gold futures market,the influence factors of international gold futures price volatility are analyzed from the perspectives of supply and demand factors,financial factors and speculation factors.The structural vector autoregression(SVAR)model is applied to investigating the direction and strength of the effects of influence factors on the international gold futures prices and the variance decomposition approach(VDA)is used to compare the contributions of these factors.The results show that the supply and demand factors still play a fundamental role in the international gold futures price volatility and the role of“China’s gold demand”is exaggerated.The financial factors and speculation factors have significant impacts on the international gold futures price volatility,which reflects that the financial property of gold becomes increasingly important.Governments and investors should pay close attention to the financial property of gold futures.
文摘Empirical research has shown that there were international spillover effects from the U.S. monetary policy to output level, net exports and price levels of each country, and the impact on prices in each country was of synchronous effect. The structural impulse response analysis showed that U.S. monetary policy could improve U.S. income and payment without damaging U.S. economic growth, but the shocks negatively affected the economic growth in the rest of the world. Hence, it's important to pay close attention to the moral risks of U.S. monetary policy to evade the global shocks caused by the "benefit-itself-at-the-expense-of-others" polices of the American government. Besides these findings, U.S. monetary policy shocks strongly affect China's trade surplus fluctuations. Based on this, we propose that the approaches of balancing China's current account could be explored efficiently from the perspective of monetary policy.
文摘The paper aims to analyze the monetary transmission model between the monetary policy and the labor market variable of unemployment.The results of the data show that,the external shocks have an important impact especially on the Romanian interest rates but also on the domestic production;however,the impact is not significant on unemployment,which proves the resilience of the domestic labor market.The central bank policy rate has a stabilizing effect on the unemployment rate in case of an increase in the euro area policy rate.