Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management pl...Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.展开更多
Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime att...Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime attribute and a key.However,determining whether an attribute is a prime attribute is a nondeterministic polynomial-time complete(NP-complete)problem,making it intractable to determine if a relation scheme is in a specific normal form.While the prime attribute problem is generally NP-complete,there are cases where identifying prime attributes is not challenging.In a relation scheme R(U,F),we partition U into four distinct subsets based on where attributes in U appear in F:U_(1)(attributes only appearing on the left-hand side of FDs),U_(2)(attributes only appearing on the right-hand side of FDs),U_(3)(attributes appearing on both sides of FDs),and U_(4)(attributes not present in F).Next,we demonstrate the necessary and sufficient conditions for a key to be the unique key of a relation scheme.Subsequently,we illustrate the features of prime attributes in U_(3) and generalize the features of common prime attributes.The findings lay the groundwork for distinguishing between complex and simple cases in prime attribute identification,thereby deepening the understanding of this problem.展开更多
Conservation and enhancement of old-growth forests are key in forest planning and policies.In order to do so,more knowledge is needed on how the attributes traditionally associated with old-growth forests are distribu...Conservation and enhancement of old-growth forests are key in forest planning and policies.In order to do so,more knowledge is needed on how the attributes traditionally associated with old-growth forests are distributed in space,what differences exist across distinct forest types and what natural or anthropic conditions are affecting the distribution of these old-growthness attributes.Using data from the Third Spanish National Forest Inventory(1997–2007),we calculated six indicators commonly associated with forest old-growthness for the plots in the territory of Peninsular Spain and Balearic Islands,and then combined them into an aggregated index.We then assessed their spatial distribution and the differences across five forest functional types,as well as the effects of ten climate,topographic,landscape,and anthropic variables in their distribution.Relevant geographical patterns were apparent,with climate factors,namely temperature and precipitation,playing a crucial role in the distribution of these attributes.The distribution of the indicators also varied across different forest types,while the effects of recent anthropic impacts were weaker but still relevant.Aridity seemed to be one of the main impediments for the development of old-growthness attributes,coupled with a negative impact of recent human pressure.However,these effects seemed to be mediated by other factors,specially the legacies imposed by the complex history of forest management practices,land use changes and natural disturbances that have shaped the forests of Spain.The results of this exploratory analysis highlight on one hand the importance of climate in the dynamic of forests towards old-growthness,which is relevant in a context of Climate Change,and on the other hand,the need for more insights on the history of our forests in order to understand their present and future.展开更多
The information from sparsely logged wellbores is currently under-utilized in reservoir simulation models and their proxies using deep and machine learning (DL/ML).This is particularly problematic for large heterogene...The information from sparsely logged wellbores is currently under-utilized in reservoir simulation models and their proxies using deep and machine learning (DL/ML).This is particularly problematic for large heterogeneous gas/oil reservoirs being considered for repurposing as gas storage reservoirs for CH_(4),CO_(2) or H_(2) and/or enhanced oil recovery technologies.Lack of well-log data leads to inadequate spatial definition of complex models due to the large uncertainties associated with the extrapolation of petrophysical rock types (PRT) calibrated with limited core data across heterogeneous and/or anisotropic reservoirs.Extracting well-log attributes from the few well logs available in many wells and tying PRT predictions based on them to seismic data has the potential to substantially improve the confidence in PRT 3D-mapping across such reservoirs.That process becomes more efficient when coupled with DL/ML models incorporating feature importance and optimized,dual-objective feature selection techniques.展开更多
To investigate the distribution and velocity attributes of gas hydrates in the northern continental slope of South China Sea, Guangzhou Marine Geological Survey conducted four-component （4C） ocean-bottom seismometer...To investigate the distribution and velocity attributes of gas hydrates in the northern continental slope of South China Sea, Guangzhou Marine Geological Survey conducted four-component （4C） ocean-bottom seismometer （OBS） surveys. A case study is presented to show the results of acquiring and processing OBS data for detecting gas hydrates. Key processing steps such as repositioning, reorientation, PZ summation, and mirror imaging are discussed. Repositioning and reorientation find the correct location and direction of nodes. PZ summation matches P- and Z-components and sums them to separate upgoing and downgoing waves. Upgoing waves are used in conventional imaging, whereas downgoing waves are used in mirror imaging. Mirror imaging uses the energy of the receiver ghost reflection to improve the illumination of shallow structures, where gas hydrates and the associated bottom-simulating reflections （BSRs） are located. We developed a new method of velocity analysis using mirror imaging. The proposed method is based on velocity scanning and iterative prestack time migration. The final imaging results are promising. When combined with the derived velocity field, we can characterize the BSR and shallow structures; hence, we conclude that using 4C OBS can reveal the distribution and velocity attributes of gas hydrates.展开更多
The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness predi...The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.展开更多
In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion ...In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion technology based on pre-stack seismic data, pre-stack P-and S-wave inversion results,and post-stack attributes.This method not only can keep the fluid information contained in pre-stack seismic data but also make use of the high SNR characteristics of post-stack data.First,we use a one-step recursive method to get the optimal attribute combination from a number of attributes.Second,we use a probabilistic neural network method to train the nonlinear relationship between log curves and seismic attributes and then use the trained samples to find the natural gamma ray distribution in the Su-14 well block and improve the resolution of seismic data.Finally,we predict the effective reservoir distribution in the Su-14 well block.展开更多
As the key technique of improved Hilbert-Huang transform （HHT）, ensemble empiri- cal mode decomposition （EEMD） has a good performance of eliminating mode mixing phenomenon, which has a strong impact on the observa...As the key technique of improved Hilbert-Huang transform （HHT）, ensemble empiri- cal mode decomposition （EEMD） has a good performance of eliminating mode mixing phenomenon, which has a strong impact on the observation of seismic information. However, the intrinsic mode functions （IMF） obtained from EEMD contain noises, so that it is required to find a more robust frequency estimation method to calculate the instantaneous frequency （IF） of IMF. For this reason, the improved HHT algorithm based on the damped instantaneous frequency （DIF） is proposed to overcome the shortage of EEMD. Compared with other IF estimation methods, the DIF has strong antinoise ability and high estimation accuracy. The test results of synthetic and real seismic data show that the proposed algorithm is feasible and effective for extracting seismic instantaneous at- tributes.展开更多
目的针对飞机货舱配载方案评估中多属性决策的复杂性,以及现有评估方法在权重确定上过度依赖专家经验导致的主观偏差,或单纯依赖客观数据忽略决策者偏好的局限性,提出一种融合主观先验与客观数据驱动的混合赋权评估模型,以提供更为合理...目的针对飞机货舱配载方案评估中多属性决策的复杂性,以及现有评估方法在权重确定上过度依赖专家经验导致的主观偏差,或单纯依赖客观数据忽略决策者偏好的局限性,提出一种融合主观先验与客观数据驱动的混合赋权评估模型,以提供更为合理、可靠的配载方案择优决策支持。方法首先,引入大型语言模型(Large language model,LLM),构建“虚拟专家委员会”,通过精心设计的提示词工程,获取多维度、多情境下的主观权重。其次,针对传统熵权法对数据分布敏感、难以有效区分指标优劣等问题,提出一种改进的数据预处理熵权法(Improved data preprocessing entropy weighting method,IDPEW),该方法结合指标值的辨识度和信息熵的均衡性来确定客观权重。最后,将LLM生成的主观权重与IDPEW计算的客观权重进行加权组合,构建综合评价函数,对飞机货舱配载方案进行全面评估和排序。结果实验结果表明,LLM模拟专家意见时最关注“装载率”(主观权重0.2250),而IDPEW方法从数据中识别出“横向不平衡度”最具区分力(客观权重0.2481)。混合赋权模型(α=0.5)有效平衡了主客观偏好,在24个方案中精准识别出综合性能最优的方案,验证了模型在复杂情境下的稳定性。结论创新性地利用LLM低成本构建“虚拟专家”获取先验知识,并通过耦合指标辨识度与均衡性的IDPEW方法,提升了客观赋权精度。该模型克服了单一赋权的局限,为飞机货舱配载方案的科学评估提供了一种兼具可解释性和实用性的新范式。展开更多
Ordovician limestone water is coal mines. In this paper, we analyze the the main source of water inrush in North China characteristic of three kinds of nonlinear seismic attributes, such as the largest lyapunov expone...Ordovician limestone water is coal mines. In this paper, we analyze the the main source of water inrush in North China characteristic of three kinds of nonlinear seismic attributes, such as the largest lyapunov exponent,fractal dimension and entropy and introduce their calculation methods. Taking the 81st and 82nd coal districts in the Xutuan coal mine as examples, we extract the three seismic attributes based on the 3D prestack migration seismic data of this area, which can display the Ordovician limestone fracture distribution in the mine. We comprehensively analyzed the three nonlinear seismic attributes and compared the results with transient electromagnetic exploration results and determined the possible Ordovician limestone aquosity distribution. This demonstrated that the nonlinear seismic attributes technology is an effective approach to predict the aquosity of Ordovician limestone.展开更多
The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risk...The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.展开更多
There are similarities and differences about the order of the attributes between English sentences and Chinese sentenc es. As a result, mistakes can often be observed; those mistakes are the results of unfamiliarity w...There are similarities and differences about the order of the attributes between English sentences and Chinese sentenc es. As a result, mistakes can often be observed; those mistakes are the results of unfamiliarity with the proper order of the attri butes. But here, special attention is paid to the EST(English for Science and Technology) translation in which their differences are much more distinct. Generally speaking, the attributes in English can be divided into pre-attributes and post-attributes in terms of their positions in a sentence. But in Chinese an attribute is usually put before a noun, and rarely put after it, so several simple comparisons are tried to find out some rules to translate English attributes into Chinese.展开更多
Contrastive linguistics is a branch of linguistics which mainly involves contrast or comparison,and it can leave us some useful insights into our problems,especially for translation work.This paper discusses similarit...Contrastive linguistics is a branch of linguistics which mainly involves contrast or comparison,and it can leave us some useful insights into our problems,especially for translation work.This paper discusses similarities and differences between English attributes and Chinese attributes from the perspective of the location,the composition,and the function,for the purpose of presenting a sound version for the original text.展开更多
Comparative study between English and Chinese attributes has been a research hotspot.The differences between English and Chinese attributes are elaborated by examples and translation strategies of English and Chinese ...Comparative study between English and Chinese attributes has been a research hotspot.The differences between English and Chinese attributes are elaborated by examples and translation strategies of English and Chinese attributes are discussed in this paper,from which the implications for translation teaching are stated at the same time.展开更多
Biochar is considered as a beneficial soil amendment for crop production. However, limited information is available on the effects of continuous applications of biochar on rice. In this study, a fixed field experiment...Biochar is considered as a beneficial soil amendment for crop production. However, limited information is available on the effects of continuous applications of biochar on rice. In this study, a fixed field experiment was conducted in the early and late rice-growing seasons from 2015 to 2017. Grain yield and yield attributes with a widely-grown rice cultivar Zhongzao 39 were compared, with and without applications of biochar in each season. The results showed that grain yield initially decreased with biochar applications in the first three seasons due to decreases in grain weight and harvest index. Although there were further relative decreases in grain weight and harvest index for rice that was supplied with biochar in the fourth to sixth seasons, grain yield was increased(by 4–10%) because of increases in sink size(spikelets per m2) and total biomass. The increased sink size in rice whose soil had been supplied with biochar in the fourth to sixth seasons was achieved by increasing panicle size(spikelets per panicle) or number of panicles, or both. Our study suggests that the positive effects of biochar application on rice yield and yield attributes depend on the duration of biochar application. Further investigations are needed to determine what are the soil and physiological processes for producing yield responses associated with ongoing applications of biochar. Also, it should be evaluated the performance of biochar application combined with other management practices, especially those can increase the grain weight and harvest index in rice production.展开更多
基金funded by NARI Group’s Independent Project of China(Grant No.524609230125)the Foundation of NARI-TECH Nanjing Control System Ltd.of China(Grant No.0914202403120020).
文摘Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.
文摘Normal forms have a significant role in the theory of relational database normalization.The definitions of normal forms are established through the functional dependency(FD)relationship between a prime or nonprime attribute and a key.However,determining whether an attribute is a prime attribute is a nondeterministic polynomial-time complete(NP-complete)problem,making it intractable to determine if a relation scheme is in a specific normal form.While the prime attribute problem is generally NP-complete,there are cases where identifying prime attributes is not challenging.In a relation scheme R(U,F),we partition U into four distinct subsets based on where attributes in U appear in F:U_(1)(attributes only appearing on the left-hand side of FDs),U_(2)(attributes only appearing on the right-hand side of FDs),U_(3)(attributes appearing on both sides of FDs),and U_(4)(attributes not present in F).Next,we demonstrate the necessary and sufficient conditions for a key to be the unique key of a relation scheme.Subsequently,we illustrate the features of prime attributes in U_(3) and generalize the features of common prime attributes.The findings lay the groundwork for distinguishing between complex and simple cases in prime attribute identification,thereby deepening the understanding of this problem.
基金supported by the Spanish Ministry of Science and Innovation project GREEN-RISK(Evaluation of past changes in ecosystem services and biodiversity in forests and restoration priorities under global change impacts-PID2020-119933RB-C21)A.C.received a pre-doctoral fellowship funded by the Spanish Ministry of Science and Innovation(PRE2021-099642).
文摘Conservation and enhancement of old-growth forests are key in forest planning and policies.In order to do so,more knowledge is needed on how the attributes traditionally associated with old-growth forests are distributed in space,what differences exist across distinct forest types and what natural or anthropic conditions are affecting the distribution of these old-growthness attributes.Using data from the Third Spanish National Forest Inventory(1997–2007),we calculated six indicators commonly associated with forest old-growthness for the plots in the territory of Peninsular Spain and Balearic Islands,and then combined them into an aggregated index.We then assessed their spatial distribution and the differences across five forest functional types,as well as the effects of ten climate,topographic,landscape,and anthropic variables in their distribution.Relevant geographical patterns were apparent,with climate factors,namely temperature and precipitation,playing a crucial role in the distribution of these attributes.The distribution of the indicators also varied across different forest types,while the effects of recent anthropic impacts were weaker but still relevant.Aridity seemed to be one of the main impediments for the development of old-growthness attributes,coupled with a negative impact of recent human pressure.However,these effects seemed to be mediated by other factors,specially the legacies imposed by the complex history of forest management practices,land use changes and natural disturbances that have shaped the forests of Spain.The results of this exploratory analysis highlight on one hand the importance of climate in the dynamic of forests towards old-growthness,which is relevant in a context of Climate Change,and on the other hand,the need for more insights on the history of our forests in order to understand their present and future.
文摘The information from sparsely logged wellbores is currently under-utilized in reservoir simulation models and their proxies using deep and machine learning (DL/ML).This is particularly problematic for large heterogeneous gas/oil reservoirs being considered for repurposing as gas storage reservoirs for CH_(4),CO_(2) or H_(2) and/or enhanced oil recovery technologies.Lack of well-log data leads to inadequate spatial definition of complex models due to the large uncertainties associated with the extrapolation of petrophysical rock types (PRT) calibrated with limited core data across heterogeneous and/or anisotropic reservoirs.Extracting well-log attributes from the few well logs available in many wells and tying PRT predictions based on them to seismic data has the potential to substantially improve the confidence in PRT 3D-mapping across such reservoirs.That process becomes more efficient when coupled with DL/ML models incorporating feature importance and optimized,dual-objective feature selection techniques.
基金supported by the National Hi-tech Research and Development Program of China(863 Program)(Grant No.2013AA092501)the China Geological Survey Projects(Grant Nos.GZH201100303 and GZH201100305)
文摘To investigate the distribution and velocity attributes of gas hydrates in the northern continental slope of South China Sea, Guangzhou Marine Geological Survey conducted four-component （4C） ocean-bottom seismometer （OBS） surveys. A case study is presented to show the results of acquiring and processing OBS data for detecting gas hydrates. Key processing steps such as repositioning, reorientation, PZ summation, and mirror imaging are discussed. Repositioning and reorientation find the correct location and direction of nodes. PZ summation matches P- and Z-components and sums them to separate upgoing and downgoing waves. Upgoing waves are used in conventional imaging, whereas downgoing waves are used in mirror imaging. Mirror imaging uses the energy of the receiver ghost reflection to improve the illumination of shallow structures, where gas hydrates and the associated bottom-simulating reflections （BSRs） are located. We developed a new method of velocity analysis using mirror imaging. The proposed method is based on velocity scanning and iterative prestack time migration. The final imaging results are promising. When combined with the derived velocity field, we can characterize the BSR and shallow structures; hence, we conclude that using 4C OBS can reveal the distribution and velocity attributes of gas hydrates.
基金supported by National Key Science and Technology Special Projects (Grant No.2008ZX05000-004)CNPC Key S and T Special Projects (Grant No.2008E-0610-10)
文摘The boundary identification and quantitative thickness prediction of channel sand bodies are always difficult in seismic exploration.We present a new method for boundary identification and quantitative thickness prediction of channel sand bodies based on seismic peak attributes in the frequency domain.Using seismic forward modeling of a typical thin channel sand body,a new seismic attribute-the ratio of peak frequency to amplitude was constructed.Theoretical study demonstrated that seismic peak frequency is sensitive to the thickness of the channel sand bodies,while the amplitude attribute is sensitive to the strata lithology.The ratio of the two attributes can highlight the boundaries of the channel sand body.Moreover,the thickness of the thin channel sand bodies can be determined using the relationship between seismic peak frequency and thin layer thickness.Practical applications have demonstrated that the seismic peak frequency attribute can depict the horizontal distribution characteristics of channels very well.The ratio of peak frequency to amplitude attribute can improve the identification ability of channel sand body boundaries.Quantitative prediction and boundary identification of channel sand bodies with seismic peak attributes in the frequency domain are feasible.
基金The National Natural Science Foundation of China and China Petroleum&Chemical Corporation Co-funded Project(Grant Nos 40839905 and 40739907)
文摘In this study area the geological conditions are complicated and the effective sandstone is very heterogeneous.The sandstones are thin and lateral and vertical variations are large.We introduce multi-attribute fusion technology based on pre-stack seismic data, pre-stack P-and S-wave inversion results,and post-stack attributes.This method not only can keep the fluid information contained in pre-stack seismic data but also make use of the high SNR characteristics of post-stack data.First,we use a one-step recursive method to get the optimal attribute combination from a number of attributes.Second,we use a probabilistic neural network method to train the nonlinear relationship between log curves and seismic attributes and then use the trained samples to find the natural gamma ray distribution in the Su-14 well block and improve the resolution of seismic data.Finally,we predict the effective reservoir distribution in the Su-14 well block.
基金supported by the National Natural Science Foundation of China(Nos.41274127,40874066,and 41301460)
文摘As the key technique of improved Hilbert-Huang transform （HHT）, ensemble empiri- cal mode decomposition （EEMD） has a good performance of eliminating mode mixing phenomenon, which has a strong impact on the observation of seismic information. However, the intrinsic mode functions （IMF） obtained from EEMD contain noises, so that it is required to find a more robust frequency estimation method to calculate the instantaneous frequency （IF） of IMF. For this reason, the improved HHT algorithm based on the damped instantaneous frequency （DIF） is proposed to overcome the shortage of EEMD. Compared with other IF estimation methods, the DIF has strong antinoise ability and high estimation accuracy. The test results of synthetic and real seismic data show that the proposed algorithm is feasible and effective for extracting seismic instantaneous at- tributes.
文摘目的针对飞机货舱配载方案评估中多属性决策的复杂性,以及现有评估方法在权重确定上过度依赖专家经验导致的主观偏差,或单纯依赖客观数据忽略决策者偏好的局限性,提出一种融合主观先验与客观数据驱动的混合赋权评估模型,以提供更为合理、可靠的配载方案择优决策支持。方法首先,引入大型语言模型(Large language model,LLM),构建“虚拟专家委员会”,通过精心设计的提示词工程,获取多维度、多情境下的主观权重。其次,针对传统熵权法对数据分布敏感、难以有效区分指标优劣等问题,提出一种改进的数据预处理熵权法(Improved data preprocessing entropy weighting method,IDPEW),该方法结合指标值的辨识度和信息熵的均衡性来确定客观权重。最后,将LLM生成的主观权重与IDPEW计算的客观权重进行加权组合,构建综合评价函数,对飞机货舱配载方案进行全面评估和排序。结果实验结果表明,LLM模拟专家意见时最关注“装载率”(主观权重0.2250),而IDPEW方法从数据中识别出“横向不平衡度”最具区分力(客观权重0.2481)。混合赋权模型(α=0.5)有效平衡了主客观偏好,在24个方案中精准识别出综合性能最优的方案,验证了模型在复杂情境下的稳定性。结论创新性地利用LLM低成本构建“虚拟专家”获取先验知识,并通过耦合指标辨识度与均衡性的IDPEW方法,提升了客观赋权精度。该模型克服了单一赋权的局限,为飞机货舱配载方案的科学评估提供了一种兼具可解释性和实用性的新范式。
文摘Ordovician limestone water is coal mines. In this paper, we analyze the the main source of water inrush in North China characteristic of three kinds of nonlinear seismic attributes, such as the largest lyapunov exponent,fractal dimension and entropy and introduce their calculation methods. Taking the 81st and 82nd coal districts in the Xutuan coal mine as examples, we extract the three seismic attributes based on the 3D prestack migration seismic data of this area, which can display the Ordovician limestone fracture distribution in the mine. We comprehensively analyzed the three nonlinear seismic attributes and compared the results with transient electromagnetic exploration results and determined the possible Ordovician limestone aquosity distribution. This demonstrated that the nonlinear seismic attributes technology is an effective approach to predict the aquosity of Ordovician limestone.
基金supported by the National Key Research and Development Program of China(Grant No.2020YFA0608904)the International Partnership Program of the Chinese Academy of Sciences(Grant Nos.060GJHZ2023079GC and 134111KYSB20160031)+1 种基金supported by the Office of Science,U.S.Department of Energy(DOE)Biological and Environmental Research as part of the Regional and Global Model Analysis program area through the Water Cycle and Climate Extremes Modeling(WACCEM)scientific focus areaoperated for DOE by Battelle Memorial Institute under contract DE-AC05-76RL01830。
文摘The global monsoon system,encompassing the Asian-Australian,African,and American monsoons,sustains two-thirds of the world’s population by regulating water resources and agriculture.Monsoon anomalies pose severe risks,including floods and droughts.Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms.Observational data reveal a 20th-century shift:increased rainfall pre-1950s,followed by aridification and partial recovery post-1980s,driven by both internal variability(e.g.,Atlantic Multidecadal Oscillation)and external forcings(greenhouse gases,aerosols),while ENSO drives interannual variability through ocean-atmosphere interactions.Future projections under greenhouse forcing suggest long-term monsoon intensification,though regional disparities and model uncertainties persist.Models indicate robust trends but struggle to quantify extremes,where thermodynamic effects(warming-induced moisture rise)uniformly boost heavy rainfall,while dynamical shifts(circulation changes)create spatial heterogeneity.Volcanic eruptions and proposed solar radiation modification(SRM)further complicate predictions:tropical eruptions suppress monsoons,whereas high-latitude events alter cross-equatorial flows,highlighting unresolved feedbacks.The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons.Critical challenges remain.Model biases and sparse 20th-century observational data hinder accurate attribution.The interplay between natural variability and anthropogenic forcings,along with nonlinear extreme precipitation risks under warming,demands deeper mechanistic insights.Additionally,SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation.Addressing these gaps necessitates enhanced observational networks,refined climate models,and interdisciplinary efforts to disentangle multiscale drivers,ultimately improving resilience strategies for monsoon-dependent regions.
文摘There are similarities and differences about the order of the attributes between English sentences and Chinese sentenc es. As a result, mistakes can often be observed; those mistakes are the results of unfamiliarity with the proper order of the attri butes. But here, special attention is paid to the EST(English for Science and Technology) translation in which their differences are much more distinct. Generally speaking, the attributes in English can be divided into pre-attributes and post-attributes in terms of their positions in a sentence. But in Chinese an attribute is usually put before a noun, and rarely put after it, so several simple comparisons are tried to find out some rules to translate English attributes into Chinese.
文摘Contrastive linguistics is a branch of linguistics which mainly involves contrast or comparison,and it can leave us some useful insights into our problems,especially for translation work.This paper discusses similarities and differences between English attributes and Chinese attributes from the perspective of the location,the composition,and the function,for the purpose of presenting a sound version for the original text.
文摘Comparative study between English and Chinese attributes has been a research hotspot.The differences between English and Chinese attributes are elaborated by examples and translation strategies of English and Chinese attributes are discussed in this paper,from which the implications for translation teaching are stated at the same time.
文摘Biochar is considered as a beneficial soil amendment for crop production. However, limited information is available on the effects of continuous applications of biochar on rice. In this study, a fixed field experiment was conducted in the early and late rice-growing seasons from 2015 to 2017. Grain yield and yield attributes with a widely-grown rice cultivar Zhongzao 39 were compared, with and without applications of biochar in each season. The results showed that grain yield initially decreased with biochar applications in the first three seasons due to decreases in grain weight and harvest index. Although there were further relative decreases in grain weight and harvest index for rice that was supplied with biochar in the fourth to sixth seasons, grain yield was increased(by 4–10%) because of increases in sink size(spikelets per m2) and total biomass. The increased sink size in rice whose soil had been supplied with biochar in the fourth to sixth seasons was achieved by increasing panicle size(spikelets per panicle) or number of panicles, or both. Our study suggests that the positive effects of biochar application on rice yield and yield attributes depend on the duration of biochar application. Further investigations are needed to determine what are the soil and physiological processes for producing yield responses associated with ongoing applications of biochar. Also, it should be evaluated the performance of biochar application combined with other management practices, especially those can increase the grain weight and harvest index in rice production.
