Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational s...Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.展开更多
1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zh...1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.展开更多
1 Introduction Sedimentary rocks archive important information for understanding how the earth system operates and how life and environments have evolved through earth history.Properly identifying characteristics of s...1 Introduction Sedimentary rocks archive important information for understanding how the earth system operates and how life and environments have evolved through earth history.Properly identifying characteristics of sedimentary rocks,along with the subsequent interpretation of depositional processes and sedimentary environments in a basin or locality.展开更多
A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay ...A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.展开更多
There is a great demand for in-situ real-time chemical sensors in the oceanographic research, to measure the chemical components under the deep sea. The ISE (Ion Selective Electrode) is commonly used as a detecting pa...There is a great demand for in-situ real-time chemical sensors in the oceanographic research, to measure the chemical components under the deep sea. The ISE (Ion Selective Electrode) is commonly used as a detecting part of deep-sea electro-chemical sensors. The paper highlights the solidification and micromation of the working and reference electrodes. The sensors of pH and H 2S with a thermal probe are accomplished after the solution of configuration of electrodes and signal processing. The sensor system has been tested successfully in the cruise of DY105-12, 14 sponsored by China Ocean Mineral Research and Exploitation Association(COMRA).展开更多
The effects of the prior austenite grain size in deep cryogenic treatment on the hardness, the structural change and the wear resistance of D6 tool steel were investigated. The wear resistance of the cryogenically tre...The effects of the prior austenite grain size in deep cryogenic treatment on the hardness, the structural change and the wear resistance of D6 tool steel were investigated. The wear resistance of the cryogenically treated samples was determined using the pin-on-disk wear machine. The microstructural characteristics and phases present in heat treated samples were determined using SEM and XRD techniques. The results showed that the retained austenite is completely transformed to martensite during the cryogenic treatment. Besides, there is an optimum grain size of which the maximum wear resistance and hardness are obtained.展开更多
Paleogeography is a discipline that studies spatial distribution and evolutionary characteristics of geographic objects in earth history(Feng,2003;Feng et al.,2012).It focuses on the sediments,organisms and environmen...Paleogeography is a discipline that studies spatial distribution and evolutionary characteristics of geographic objects in earth history(Feng,2003;Feng et al.,2012).It focuses on the sediments,organisms and environmental proxies,most of which are preserved in the rocks.However,a large amount of this geological and biological information was no longer preserved after the geological process of burial.展开更多
Considering the recent developments in deep learning, it has become increasingly important to verify what methods are valid for the prediction of multivariate time-series data. In this study, we propose a novel method...Considering the recent developments in deep learning, it has become increasingly important to verify what methods are valid for the prediction of multivariate time-series data. In this study, we propose a novel method of time-series prediction employing multiple deep learners combined with a Bayesian network where training data is divided into clusters using K-means clustering. We decided how many clusters are the best for K-means with the Bayesian information criteria. Depending on each cluster, the multiple deep learners are trained. We used three types of deep learners: deep neural network (DNN), recurrent neural network (RNN), and long short-term memory (LSTM). A naive Bayes classifier is used to determine which deep learner is in charge of predicting a particular time-series. Our proposed method will be applied to a set of financial time-series data, the Nikkei Average Stock price, to assess the accuracy of the predictions made. Compared with the conventional method of employing a single deep learner to acquire all the data, it is demonstrated by our proposed method that F-value and accuracy are improved.展开更多
1.Introduction.Since the Industrial Revolution,the partial pressure of atmospheric carbon dioxide(pCO_(2))has increased markedly,rising from approximately 280 ppm(1 ppm=1μL/L)to about 420 ppm.This escalation has inte...1.Introduction.Since the Industrial Revolution,the partial pressure of atmospheric carbon dioxide(pCO_(2))has increased markedly,rising from approximately 280 ppm(1 ppm=1μL/L)to about 420 ppm.This escalation has intensified global warming,with 2024 the hottest year on record since 1850.The global mean temperature now stands 1.46℃ above the pre-industrial average(1850-1900),a value already approaching the 1.5℃ threshold set by the Paris Agreement(NOAA,2025).展开更多
基金The Key R&D Project of Jilin Province,Grant/Award Number:20230201067GX。
文摘Extracting typical operational scenarios is essential for making flexible decisions in the dispatch of a new power system.A novel deep time series aggregation scheme(DTSAs)is proposed to generate typical operational scenarios,considering the large amount of historical operational snapshot data.Specifically,DTSAs analyse the intrinsic mechanisms of different scheduling operational scenario switching to mathematically represent typical operational scenarios.A Gramian angular summation field-based operational scenario image encoder was designed to convert operational scenario sequences into highdimensional spaces.This enables DTSAs to fully capture the spatiotemporal characteristics of new power systems using deep feature iterative aggregation models.The encoder also facilitates the generation of typical operational scenarios that conform to historical data distributions while ensuring the integrity of grid operational snapshots.Case studies demonstrate that the proposed method extracted new fine-grained power system dispatch schemes and outperformed the latest high-dimensional feature-screening methods.In addition,experiments with different new energy access ratios were conducted to verify the robustness of the proposed method.DTSAs enable dispatchers to master the operation experience of the power system in advance,and actively respond to the dynamic changes of the operation scenarios under the high access rate of new energy.
基金granted by the National Science&Technology Major Projects of China(Grant No.2016ZX05033).
文摘1 Introduction Information technology has been playing an ever-increasing role in geoscience.Sphisicated database platforms are essential for geological data storage,analysis and exchange of Big Data(Feblowitz,2013;Zhang et al.,2016;Teng et al.,2016;Tian and Li,2018).The United States has built an information-sharing platform for state-owned scientific data as a national strategy.
文摘1 Introduction Sedimentary rocks archive important information for understanding how the earth system operates and how life and environments have evolved through earth history.Properly identifying characteristics of sedimentary rocks,along with the subsequent interpretation of depositional processes and sedimentary environments in a basin or locality.
基金Supported by the National Natural Science Foundation of China under Grant No 11174235
文摘A method of source depth estimation based on the multi-path time delay difference is proposed. When the minimum time arrivals in all receiver depths are snapped to a certain time on time delay-depth plane, time delay arrivals of surface-bottom reflection and bottom-surface reflection intersect at the source depth. Two hydrophones deployed vertically with a certain interval are required at least. If the receiver depths are known, the pair of time delays can be used to estimate the source depth. With the proposed method the source depth can be estimated successfully in a moderate range in the deep ocean without complicated matched-field calculations in the simulations and experiments.
基金The research program was financially supported by the Joint Program of Chinese 863 Project (Grant No. 2001AA612020 4) and the sea trial support from COMRA, China Ocean Mineral Research and Exploitation Association as well.
文摘There is a great demand for in-situ real-time chemical sensors in the oceanographic research, to measure the chemical components under the deep sea. The ISE (Ion Selective Electrode) is commonly used as a detecting part of deep-sea electro-chemical sensors. The paper highlights the solidification and micromation of the working and reference electrodes. The sensors of pH and H 2S with a thermal probe are accomplished after the solution of configuration of electrodes and signal processing. The sensor system has been tested successfully in the cruise of DY105-12, 14 sponsored by China Ocean Mineral Research and Exploitation Association(COMRA).
文摘The effects of the prior austenite grain size in deep cryogenic treatment on the hardness, the structural change and the wear resistance of D6 tool steel were investigated. The wear resistance of the cryogenically treated samples was determined using the pin-on-disk wear machine. The microstructural characteristics and phases present in heat treated samples were determined using SEM and XRD techniques. The results showed that the retained austenite is completely transformed to martensite during the cryogenic treatment. Besides, there is an optimum grain size of which the maximum wear resistance and hardness are obtained.
基金granted by the National Science and Technology Major Project of China(Grant No.2017ZX05035002-001)the National Natural Science Foundation of China(Grant Nos.41802017 and 41725007)+1 种基金the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB26000000)the State Key Laboratory of Palaeobiology and Stratigraphy(Grant No.20172112).
文摘Paleogeography is a discipline that studies spatial distribution and evolutionary characteristics of geographic objects in earth history(Feng,2003;Feng et al.,2012).It focuses on the sediments,organisms and environmental proxies,most of which are preserved in the rocks.However,a large amount of this geological and biological information was no longer preserved after the geological process of burial.
文摘Considering the recent developments in deep learning, it has become increasingly important to verify what methods are valid for the prediction of multivariate time-series data. In this study, we propose a novel method of time-series prediction employing multiple deep learners combined with a Bayesian network where training data is divided into clusters using K-means clustering. We decided how many clusters are the best for K-means with the Bayesian information criteria. Depending on each cluster, the multiple deep learners are trained. We used three types of deep learners: deep neural network (DNN), recurrent neural network (RNN), and long short-term memory (LSTM). A naive Bayes classifier is used to determine which deep learner is in charge of predicting a particular time-series. Our proposed method will be applied to a set of financial time-series data, the Nikkei Average Stock price, to assess the accuracy of the predictions made. Compared with the conventional method of employing a single deep learner to acquire all the data, it is demonstrated by our proposed method that F-value and accuracy are improved.
基金supported by the National Natural Science Foundation of China(Grant Nos.42425305,42293290,and 42172216).
文摘1.Introduction.Since the Industrial Revolution,the partial pressure of atmospheric carbon dioxide(pCO_(2))has increased markedly,rising from approximately 280 ppm(1 ppm=1μL/L)to about 420 ppm.This escalation has intensified global warming,with 2024 the hottest year on record since 1850.The global mean temperature now stands 1.46℃ above the pre-industrial average(1850-1900),a value already approaching the 1.5℃ threshold set by the Paris Agreement(NOAA,2025).
