Prediction has become more and more difficult in mineral exploration, especially in the mature exploration environment such as Tongling copper district. For enhancing predictive discovery of hidden ore deposits in suc...Prediction has become more and more difficult in mineral exploration, especially in the mature exploration environment such as Tongling copper district. For enhancing predictive discovery of hidden ore deposits in such mature environment, the key strategies which should be adopted include the innovation of the exploration models, application of the advanced exploration techniques and integration of multiple sets of information. The innovation of the exploration models should incorporate the new metallogenic concepts that are based on the geodynamic anatomization. The advanced techniques applied in the mature exploration environment should aim at the speciality and complexity of the geological setting and working environments. The information synthesis is to integrate multiple sets of data for giving a more credible and visual prospectivity map by using the geographic imformation system(GIS) and several mathematical methods, such as weight of evidence and fuzzy logic, which can extract useful information from every set of data as much as possible. Guided by these strategies, a predictive exploration in Fenghuangshan ore field of Tongling copper district was implemented, and a hidden ore deposit was discovered.展开更多
Enviromics refers to the characterization of micro-and macroenvironments based on large-scale environmental datasets.By providing genotypic recommendations with predictive extrapolation at a site-specific level,enviro...Enviromics refers to the characterization of micro-and macroenvironments based on large-scale environmental datasets.By providing genotypic recommendations with predictive extrapolation at a site-specific level,enviromics could inform plant breeding decisions across varying conditions and anticipate productivity in a changing climate.Enviromics-based integration of statistics,envirotyping(i.e.,determining environmental factors),and remote sensing could help unravel the complex interplay of genetics,environment,and management.To support this goal,exhaustive envirotyping to generate precise environmental profiles would significantly improve predictions of genotype performance and genetic gain in crops.Already,informatics management platforms aggregate diverse environmental datasets obtained using optical,thermal,radar,and light detection and ranging(LiDAR)sensors that capture detailed information about vegetation,surface structure,and terrain.This wealth of information,coupled with freely available climate data,fuels innovative enviromics research.While enviromics holds immense potential for breeding,a few obstacles remain,such as the need for(1)integrative methodologies to systematically collect field data to scale and expand observations across the landscape with satellite data;(2)state-of-the-art AI models for data integration,simulation,and prediction;(3)cyberinfrastructure for processing big data across scales and providing seamless interfaces to deliver forecasts to stakeholders;and(4)collaboration and data sharing among farmers,breeders,physiologists,geoinformatics experts,and programmers across research institutions.Overcoming these challenges is essential for leveraging the full potential of big data captured by satellites to transform 21st century agriculture and crop improvement through enviromics.展开更多
Data analytics of an information system is conducted based on a Markov decision process(MDP)and a partially observable Markov decision process(POMDP)in this paper.Data analytics over a finite planning horizon and an i...Data analytics of an information system is conducted based on a Markov decision process(MDP)and a partially observable Markov decision process(POMDP)in this paper.Data analytics over a finite planning horizon and an infinite planning horizon for a discounted MDP is performed,respectively.Value iteration(VI),policy iteration(PI),and Q-learning are utilized in the data analytics for a discounted MDP over an infinite planning horizon to evaluate the validity of the MDP model.The optimal policy to minimize the total expected cost of states of the information system is obtained based on the MDP.In the analytics for a discounted POMDP over an infinite planning horizon of the information system,the effects of various parameters on the total expected cost of the information system are studied.展开更多
This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierar...This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.展开更多
An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering o...An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a target.After acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized architecture.To facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff tracking.Additionally,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its target.Sufficient experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.展开更多
A general method for assessing local influence of minor perturbations of prior in Bayesian analysis is developed in this paper. U8ing some elementary ideas from differelltial geometryl we provide a unified approach fo...A general method for assessing local influence of minor perturbations of prior in Bayesian analysis is developed in this paper. U8ing some elementary ideas from differelltial geometryl we provide a unified approach for handling a variety of problexns of local prior influence. AS applications, we discuss the local influence of small perturbstions of normal-gamma prior density in linear model and investigate local prior influence from the predictive view.展开更多
基金Project(2001CB409809) supported by the National Key Foundmental Research and Development Program of Chinaproject(1042610) supported by the Key Program of the Education Ministry of China
文摘Prediction has become more and more difficult in mineral exploration, especially in the mature exploration environment such as Tongling copper district. For enhancing predictive discovery of hidden ore deposits in such mature environment, the key strategies which should be adopted include the innovation of the exploration models, application of the advanced exploration techniques and integration of multiple sets of information. The innovation of the exploration models should incorporate the new metallogenic concepts that are based on the geodynamic anatomization. The advanced techniques applied in the mature exploration environment should aim at the speciality and complexity of the geological setting and working environments. The information synthesis is to integrate multiple sets of data for giving a more credible and visual prospectivity map by using the geographic imformation system(GIS) and several mathematical methods, such as weight of evidence and fuzzy logic, which can extract useful information from every set of data as much as possible. Guided by these strategies, a predictive exploration in Fenghuangshan ore field of Tongling copper district was implemented, and a hidden ore deposit was discovered.
基金R.T.R.,L.L.P.,and G.E.M.thank the Brazilian agencies Coordenac¸ao de Aperfeic¸oamento de Pessoal de Nıvel Superior(CAPES)and Conselho Nacional de Desenvolvimento Cientıfico e Tecnologico(CNPq)for the financial support,which was instrumental in the successful execution of this project.L.H.was supported through an ARC Future Fellowship(FT220100350)from the Australian Research Council.C.H.A.was supported by The University of Colorado Boulder Grand ChallengeCIRES Earth Lab.Y.X.was supported by the Agricultural Science and Technology Innovation Program(ASTIP)of the Chinese Academy of Agricultural Sciences,Shenzhen Science and Technology Program(KQTD202303010928390070)Hebei Science and Technology Program(215A7612D),and the Provincial Technology Innovation Program of Shandong,China.
文摘Enviromics refers to the characterization of micro-and macroenvironments based on large-scale environmental datasets.By providing genotypic recommendations with predictive extrapolation at a site-specific level,enviromics could inform plant breeding decisions across varying conditions and anticipate productivity in a changing climate.Enviromics-based integration of statistics,envirotyping(i.e.,determining environmental factors),and remote sensing could help unravel the complex interplay of genetics,environment,and management.To support this goal,exhaustive envirotyping to generate precise environmental profiles would significantly improve predictions of genotype performance and genetic gain in crops.Already,informatics management platforms aggregate diverse environmental datasets obtained using optical,thermal,radar,and light detection and ranging(LiDAR)sensors that capture detailed information about vegetation,surface structure,and terrain.This wealth of information,coupled with freely available climate data,fuels innovative enviromics research.While enviromics holds immense potential for breeding,a few obstacles remain,such as the need for(1)integrative methodologies to systematically collect field data to scale and expand observations across the landscape with satellite data;(2)state-of-the-art AI models for data integration,simulation,and prediction;(3)cyberinfrastructure for processing big data across scales and providing seamless interfaces to deliver forecasts to stakeholders;and(4)collaboration and data sharing among farmers,breeders,physiologists,geoinformatics experts,and programmers across research institutions.Overcoming these challenges is essential for leveraging the full potential of big data captured by satellites to transform 21st century agriculture and crop improvement through enviromics.
文摘Data analytics of an information system is conducted based on a Markov decision process(MDP)and a partially observable Markov decision process(POMDP)in this paper.Data analytics over a finite planning horizon and an infinite planning horizon for a discounted MDP is performed,respectively.Value iteration(VI),policy iteration(PI),and Q-learning are utilized in the data analytics for a discounted MDP over an infinite planning horizon to evaluate the validity of the MDP model.The optimal policy to minimize the total expected cost of states of the information system is obtained based on the MDP.In the analytics for a discounted POMDP over an infinite planning horizon of the information system,the effects of various parameters on the total expected cost of the information system are studied.
基金supported by the National Natural Science Foundation of China(Grand No.52202484)the Hebei Natural Science Foundation(Grand No.F2021203118)+1 种基金the Beijing Natural Science Foundation(Grand No.J210007)the Science and Technology Project of Hebei Education Department(Grand No.QN2022093).
文摘This paper aims to answer how to use traffic information to design energy management strategies for fuel cell buses in a networked environment.For the buses entering the bus stops scenario,this paper proposes a hierarchical energy management strategy for fuel cell buses,which considers the traffic information near the bus stops.In the upper-level trajectory planning stage,the optimal SOC trajectory under various historical traffic conditions is solved through dynamic planning.The traffic information and the best SOC trajectory are mapped through BiLSTM,which can achieve fast,real-time long-term SOC reference.In the lower-level real-time predictive energy management strategy,the optimal SOC is used as the state reference to guide the predictive energy management of fuel cell buses when entering the bus stops.Simulation results show that compared with the strategy without SOC trajectory reference,the life cost of the proposed strategy is reduced by 13.8%,and the total cost is reduced by 3.61%.The SOC of the proposed strategy is closer to the DP optimal solution.
基金supported in part by the National Natural Science Foundation of China(Nos.62022092 and 61790550).
文摘An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a target.After acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized architecture.To facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff tracking.Additionally,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its target.Sufficient experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.
文摘A general method for assessing local influence of minor perturbations of prior in Bayesian analysis is developed in this paper. U8ing some elementary ideas from differelltial geometryl we provide a unified approach for handling a variety of problexns of local prior influence. AS applications, we discuss the local influence of small perturbstions of normal-gamma prior density in linear model and investigate local prior influence from the predictive view.
