A Level考试素有“英国高考”之称。其制度演进大致经历了发轫与探索、扩张与调适、回归与重塑三个阶段,其主要变革内容包括四个方面:组织形式从年终末考的线性考试模式发展为一年多考的模块化考试,再回归线性考试模式;考试评价从常模...A Level考试素有“英国高考”之称。其制度演进大致经历了发轫与探索、扩张与调适、回归与重塑三个阶段,其主要变革内容包括四个方面:组织形式从年终末考的线性考试模式发展为一年多考的模块化考试,再回归线性考试模式;考试评价从常模参照转变为标准参照,评价手段逐步优化;考试要求从注重学科深度转变为强调知识广度,再发展为追求广度和深度并重;考试内容从偏重学术性转变为普职并重,再发展为职普融通和强调基础学科。变革的动因既有来自外部的国际竞争加剧和国内政党轮替,也有来自内部的文化价值观驱动和考试选才效度追求。A Level考试制度对我国高考改革有一定启发,我国可结合国情,以基础学科为支点、职普融通为路径、多样化的考试选择为依托、预测效度为导向,开展本土化探索。展开更多
The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the...The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.展开更多
Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that empl...Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.展开更多
This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fati...This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.展开更多
Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 Dec...Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 December 2025,Hainan officially launched island-wide special customs operations,commonly referred to as“customs closure.”From that date,goods entering or leaving the island,except those traded with the Chinese mainland,are subject to simplified customs procedures and potentially reduced or zero tariffs.展开更多
During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once ag...During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.展开更多
Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi...Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.展开更多
To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal test...To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal tests on rock samples to investigate the correlations between macro-and meso-level mechanical parameters of rock-like bonded granular materials. Then based on the artificial intelligent technology, the intelligent prediction systems for nine meso-level mechanical parameters of PFC models were obtained by creating, training and testing the prediction models with the set of data got from the orthogonal tests. Lastly the prediction systems were used to predict the meso-level mechanical parameters of one kind of sandy mudstone, and according to the predicted results the macroscopic properties of the rock were obtained by numerical tests. The maximum relative error between the numerical test results and real rock properties is 3.28% which satisfies the precision requirement in engineering. It shows that this paper provides a fast and accurate method for the determination of meso-level mechanical parameters of PFC models.展开更多
Ligaments are densely connective soft tissues capable of maintaining stability and function of knee joint.As an important factor,the constitutive relation of ligament would affect its biomechanics and further play an ...Ligaments are densely connective soft tissues capable of maintaining stability and function of knee joint.As an important factor,the constitutive relation of ligament would affect its biomechanics and further play an essential role in the research on ligament injury,healing and treatment.The objective of this paper is to provide an overview of the current research on ligament constitutive relations on the macro,meso,and micro levels as well as the anatomy and histological structure of ligament.Some studies of biomechanical behaviors during ligament injury and healing periods have also been investigated.Based on the research on ligament constitutive relation in the past three decades,a discussion of some research perspectives is also presented,such as a validated accurate measuring method of in situ strain in ligament,a new constitutive relation involving the distribution of ultra-structural properties,and a rational estimation of ligament injury and healing process by the change of its ultra-structural or histological characteristics.展开更多
风场预报是智能网格预报的重要支撑,提高风场预报准确率,能够为风能预报提供核心保障。在综合评估2023年汛期CMA-MESO 3 km(China Meteorological Administration Mesoscale Model at 3 km resolution)模式在山西逐小时10 m风预报能力...风场预报是智能网格预报的重要支撑,提高风场预报准确率,能够为风能预报提供核心保障。在综合评估2023年汛期CMA-MESO 3 km(China Meteorological Administration Mesoscale Model at 3 km resolution)模式在山西逐小时10 m风预报能力的基础上,基于自适应Kalman滤波方法,开展针对纬向风(U)、经向风(V)的客观订正,以期建立适应山西复杂地形特征的客观预报方案,促进国产模式本地化业务应用。结果表明:①全风速预报偏大,预报误差呈“单峰型”日变化,峰值出现在18:00-20:00,正偏差主要位于忻定和太原盆地以及山西南部。②U、V预报误差与预报值呈显著正相关,需考虑不同强度预报风速误差随时效变化的特征,避免订正不足或过订正。③Kalman滤波方案(KM)订正幅度小且不稳定,订正后均方根误差R MSE削减不足6%,准确率提升不足2%。④基于动态分级的改进方案(CBKM)突破KM订正瓶颈,更准确地估计系统误差并有效订正,更好再现不同地区风速日变化,平均误差M E趋近0,R MSE削减32.8%,风向、风速预报准确率分别提升8.29%、7.92%,峰值时刻订正率达83.49%。展开更多
Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels...Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels and mineralization remains limited.In this study,we summarize the deformation patterns and associated mineral deposits observed at different crustal levels(i.e.,surface,shallow,middle,and deep structural levels,corresponding to depths of<2,2-8,8-15,and>15 km,respectively).Furthermore,we examine the genetic association between structural levels and metallogenesis,demonstrating that distinct structural levels are linked to specific types of mineralization.Key factors that vary across crustal levels include temperature,pressure,and fluid circulation.Ore-forming processes involve interactions between structures and fluids under varying temperatures and pressures.Structural levels influence mineralization by controlling the temperatures,pressures,and deformation mechanisms that drive the activation,migration,and enrichment of ore-forming materials.展开更多
Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based ...Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.展开更多
基金supported by the China National Science Foundation(No.42130506,42071031)the Special Technology Innovation Fund of Carbon Peak and Carbon Neutrality in Jiangsu Province(BK20231515)+1 种基金the Spanish Government grant PID2022-140808NB-I00 funded by MICIU/AEI/https://doi.org/10.13039/501100011033the Catalan Government grants SGR 2021-1333 and AGAUR2023 CLIMA 00118.
文摘The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change.
基金Project(42077244)supported by the National Natural Science Foundation of ChinaProject(2020-05)supported by the Open Research Fund of Guangdong Provincial Key Laboratory of Deep Earth Sciences and Geothermal Energy Exploitation and Utilization,China。
文摘Accurate prediction of rockburst intensity levels is crucial for ensuring the safety of deep hard rock engineering construction.This paper introduced an expert system for rockburst intensity level prediction that employs machine learning algorithms as the basis for its inference rules.The system comprises four modules:a database,a repository,an inference engine,and an interpreter.A database containing 1114 rockburst cases was used to construct 357 datasets that serve as the repository for the expert system.Additionally,19 types of machine learning algorithms were used to establish 6783 micro-models to construct cognitive rules within the inference engine.By integrating probability theory and marginal analysis,a fuzzy scoring method based on the SoftMax function was developed and applied to the interpreter for rockburst intensity level prediction,effectively restoring the continuity of rockburst characteristics.The research results indicate that ensemble algorithms based on decision trees are more effective in capturing the characteristics of rockburst.Key factors for accurate prediction of rockburst intensity include uniaxial compressive strength,elastic energy index,the maximum principal stress,tangential stress,and their composite indicators.The accuracy of the proposed rockburst intensity level prediction expert system was verified using 20 engineering rockburst cases,with predictions aligning closely with the actual rockburst intensity levels.
基金supported by National Natural Science Foundation of China[NO.11932013].
文摘This study aims to explore the impact of fatigue induced by different limb exercises on cerebral cortical oxygenation levels and functional connectivity strength using functional near-infrared spectroscopy(fNIRS).Fatigue was induced using an upper limb ergometer or a lower limb ergometer,with the load increasing gradually each minute.fNIRS covering the prefrontal cortex and motor cortex were used to collect data during the resting state,both before and after fatigue induction.A two-way ANOVA was conducted to examine differences in oxyhemoglobin(HbO_(2))and functional connectivity before and after fatigue induction in both groups,with the significance level set at 0.05.Exercise-induced fatigue in both the upper and lower limbs leads to a significant decrease in cerebral cortical oxygenation levels.Upper limb fatigue leads to a significant reduction in functional connectivity,there were significant decreases in connectivity within the motor cortex,between the motor cortex and frontal regions,and between the right ventrolateral prefrontal cortex and other frontal regions.Conversely,no significant changes were observed before and after lower limb fatigue.Future studies should focus on examining the extent to which how changes in the cerebral cortex,induced by exercise fatigue,are linked to exercise-and/or performance-related outcomes.
文摘Hainan Province in south China is the country’s second-largest island and the largest free trade port by area.It has entered a historic phase in China’s drive to promote high-level institutional opening up.On 18 December 2025,Hainan officially launched island-wide special customs operations,commonly referred to as“customs closure.”From that date,goods entering or leaving the island,except those traded with the Chinese mainland,are subject to simplified customs procedures and potentially reduced or zero tariffs.
文摘During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.
基金Under the auspices of the National Key Research and Development Program of China(No.2024YFC3713102)。
文摘Groundwater level(GWL)is a key indicator used to accurately assess groundwater resources and form the foundation for ef-fective groundwater management.This paper integrates a Gate Recurrent Unit(GRU)model with a Multi-head Self-attention mechan-ism(MSAM-GRU)to simulate GWLs in both confined and unconfined aquifers simultaneously.The model innovatively captures the lag times between GWLs in the unconfined aquifer and precipitation,as well as between GWLs in the confined aquifer and the upper aquifer.We have assessed the effectiveness of the proposed model using a case study in the Beijing Plain,China from January 2005 to December 2020.With the consideration of lag times,the results indicated that the MSAM-GRU model exhibits a maximum 67%and 73%reduction in RMSE compared to the Attention mechanism-GRU(AM-GRU)and GRU model,respectively.MSAM-GRU model exhibited a 31%reduction in RMSE and a 0.12 increase in R^(2) compared to the same model that do not account for lag time.In Region I,the shortest lag time of GWL in the unconfined aquifer was two months,while that in the confined aquifer was three months,indicating a longer delayed response in the confined aquifer.MSAM-GRU model considering lag time,was then applied to simulate the GWLs in the unconfined aquifer under different scenarios and to analyze whether GWL fluctuations affect subway operations.The simulation res-ults showed that under the scenario 1,the GWL in the unconfined aquifer would rise above the depth of subway station floor,threaten-ing the operation of subways.This study can provide reliable technical support for the accurate simulation of GWLs in multi-aquifer systems.
基金the National Natural Science Foundation of China (Nos. 50674083 and 51074162) for its financial support
文摘To solve the problems of blindness and inefficiency existing in the determination of meso-level mechanical parameters of particle flow code (PFC) models, we firstly designed and numerically carried out orthogonal tests on rock samples to investigate the correlations between macro-and meso-level mechanical parameters of rock-like bonded granular materials. Then based on the artificial intelligent technology, the intelligent prediction systems for nine meso-level mechanical parameters of PFC models were obtained by creating, training and testing the prediction models with the set of data got from the orthogonal tests. Lastly the prediction systems were used to predict the meso-level mechanical parameters of one kind of sandy mudstone, and according to the predicted results the macroscopic properties of the rock were obtained by numerical tests. The maximum relative error between the numerical test results and real rock properties is 3.28% which satisfies the precision requirement in engineering. It shows that this paper provides a fast and accurate method for the determination of meso-level mechanical parameters of PFC models.
基金supported by the National Natural Science Foundation of China(No.51275267)
文摘Ligaments are densely connective soft tissues capable of maintaining stability and function of knee joint.As an important factor,the constitutive relation of ligament would affect its biomechanics and further play an essential role in the research on ligament injury,healing and treatment.The objective of this paper is to provide an overview of the current research on ligament constitutive relations on the macro,meso,and micro levels as well as the anatomy and histological structure of ligament.Some studies of biomechanical behaviors during ligament injury and healing periods have also been investigated.Based on the research on ligament constitutive relation in the past three decades,a discussion of some research perspectives is also presented,such as a validated accurate measuring method of in situ strain in ligament,a new constitutive relation involving the distribution of ultra-structural properties,and a rational estimation of ligament injury and healing process by the change of its ultra-structural or histological characteristics.
文摘风场预报是智能网格预报的重要支撑,提高风场预报准确率,能够为风能预报提供核心保障。在综合评估2023年汛期CMA-MESO 3 km(China Meteorological Administration Mesoscale Model at 3 km resolution)模式在山西逐小时10 m风预报能力的基础上,基于自适应Kalman滤波方法,开展针对纬向风(U)、经向风(V)的客观订正,以期建立适应山西复杂地形特征的客观预报方案,促进国产模式本地化业务应用。结果表明:①全风速预报偏大,预报误差呈“单峰型”日变化,峰值出现在18:00-20:00,正偏差主要位于忻定和太原盆地以及山西南部。②U、V预报误差与预报值呈显著正相关,需考虑不同强度预报风速误差随时效变化的特征,避免订正不足或过订正。③Kalman滤波方案(KM)订正幅度小且不稳定,订正后均方根误差R MSE削减不足6%,准确率提升不足2%。④基于动态分级的改进方案(CBKM)突破KM订正瓶颈,更准确地估计系统误差并有效订正,更好再现不同地区风速日变化,平均误差M E趋近0,R MSE削减32.8%,风向、风速预报准确率分别提升8.29%、7.92%,峰值时刻订正率达83.49%。
基金supported by National Key Research and Development Program of China(Grant Nos.2022YFF0800903 and 2024YFC2909905)the National Natural Science Foundation of China(NSFC)(Grant Nos.42261144669,42262026,and 42273073).
文摘Metallogenic research on structural levels can reveal vertical patterns of mineralization and facilitate the deep exploration of economic minerals.However,research focusing on the correlation between structural levels and mineralization remains limited.In this study,we summarize the deformation patterns and associated mineral deposits observed at different crustal levels(i.e.,surface,shallow,middle,and deep structural levels,corresponding to depths of<2,2-8,8-15,and>15 km,respectively).Furthermore,we examine the genetic association between structural levels and metallogenesis,demonstrating that distinct structural levels are linked to specific types of mineralization.Key factors that vary across crustal levels include temperature,pressure,and fluid circulation.Ore-forming processes involve interactions between structures and fluids under varying temperatures and pressures.Structural levels influence mineralization by controlling the temperatures,pressures,and deformation mechanisms that drive the activation,migration,and enrichment of ore-forming materials.
基金supported by the National Key R&D Program of China(Grant No.2022YFC3005401)the National Natural Science Foundation of China(Grant No.52239009)。
文摘Accurate prediction of water level changes in reservoirs is crucial for optimizing the operation of reservoir projects and ensuring their safety.This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms.By integrating the adaptive complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)method and fuzzy entropy(FE)with the new and highly efficient Runge–Kuta optimizer(RUN),adaptive parameter optimization for the support vector machine(SVM)and radial basis function neural network(RBFNN)algorithms was achieved.Regression prediction was conducted on the two reconstructed sequences using SVM and RBFNN according to their respective features.This approach improved the accuracy and stability of predictions.In terms of accuracy,the combined model outperformed single models,with the determination coefficient,root mean square error,and mean absolute error values of 0.9975,0.2418 m,and 0.1616 m,respectively.In terms of stability,the model predicted more consistently in training and testing periods,with stable overall prediction accuracy and a better adaptive ability to complex datasets.The case study demonstrated that the combined prediction model effectively addressed the environmental factors affecting reservoir water levels,leveraged the strength of each predictive method,compensated for their limitations,and clarified the impacts of environmental factors on reservoir water levels.
