The United Nations Framework Convention on Climate Change （UNFCCC） requires reporting net carbon stock changes and anthropogenic greenhouse gas emissions, including those related to forests. This paper describes the...The United Nations Framework Convention on Climate Change （UNFCCC） requires reporting net carbon stock changes and anthropogenic greenhouse gas emissions, including those related to forests. This paper describes the status of carbon stocks in sub tropical forests of Pakistan. There are two major sub types in subtropical forests of Pakistan viz a viz Subtropical Chir Pine and Subtropical broadleaved forests. A network of sample plots was laid out in four selected site. Two sites were selected from sub tropical Chir Pine （Pinus roxburghii） forests and two from Subtropical broadleaved forests. Measurement and data acquisition protocols were developed specifically for the inventory car- ried out from 2005 to 2010. In total 261 plots （each of lha.） were established. Estimation of diameter, basal area, height, volume and biomass was carried out to estimate carbon stocks in each of the four carbon pools of above- and below-ground live biomass. Soil carbon stocks were also determined by doing soil sampling. In mature （-100 years old） pine forest stand at Ghoragali and Lehterar sites, a mean basal area of 30.38 and 26.11 m2.ha-1 represented mean volume of 243 and 197 m3·ha-1, respectively. The average biomass （t.ha-1） was 237 in Ghoragali site and 186 tha-1 in Lehterar site, which is equal to 128 and 100 t·ha-1 including soil C. However, on average basis both the forests have 114.5± 2.26 t.ha-1 of carbon stock which comprises of 92% in tree biomass and only 8% in the top soils. In mixed broadleaved evergreen forests a mean basal area （m2.ha-1）was 3.06 at Kherimurat with stem volume of 12.86 and 2.65 at Sohawa with stem volume of 11.40 m3.ha-1. The average upper and under storey biomass （t·ha-1） was 50.93 in Kherimurat site and 40.43 t.ha-1 in Sohawa site, which is equal to 31.18 and 24.36 t ·ha-1 including soil C stocks. This study provides a protocol monitoring biomass and carbon stocks and valuable baseline data for in Pakistan＇s managed and unmanaged sub-tropical forests.展开更多
The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role...The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role in regulating the population dynamics of the I. argentinus population. This study develops an environmentally dependent surplus production（EDSP） model to evaluate the stock abundance of I. argentines during the period of 2000 to 2010. The environmental factors（favorable spawning habitat areas with sea surface temperature of 16–18°C） were assumed to be closely associated with carrying capacity（K） in the EDSP model. Deviance Information Criterion（DIC） values suggest that the estimated EDSP model with environmental factors fits the data better than a Schaefer surplus model without environmental factors under uniform and normal scenarios.The EDSP model estimated a maximum sustainable yield（MSY） from 351 600 t to 685 100 t and a biomass from 1 322 400 t to1 803 000 t. The fishing mortality coefficient of I. argentinus from 2000 to 2010 was smaller than the values of F（0.1） and F（MSY）. Furthermore, the time series biomass plot of I. argentinus from 2000 to 2010 shows that the biomass of I.argentinus and this fishery were in a good state and not presently experiencing overfishing. This study suggests that the environmental conditions of the habitat should be considered within squid stock assessment and management.展开更多
The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process ...The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv.展开更多
On the basis of the analysis of classical stock model, according to the limitation of the model, the article puts forward the revision of classical model and enforces the applicability of the stock model.
Through analyzing the desired characteristics of fittings in a nuclear power plant, the representative random stock models are built, and forecast methods about the desired probability of fittings are discussed secon...Through analyzing the desired characteristics of fittings in a nuclear power plant, the representative random stock models are built, and forecast methods about the desired probability of fittings are discussed secondly, the design of the plant fittings stock decision support system (FSDSS) is given. Then the main features of this system and function modules are introduced, and the special emphasis on organization of a database and composition and memory of a model base is given.展开更多
This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to...This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to find out the alpha excess return relative to the market in the case of short stock index futures as a hedge in the Chinese market.展开更多
This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect ...This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect of different distributional assumption on the GARCH models. The data we analyze are the daily stocks indexes for Shenzhen Stock Exchange （SSE） in China from April 3^rd, 1991 to April 14^th, 2005. We find that improvements of the overall estimation are achieved when asymmetric GARCH models are used with student-t distribution and generalized error distribution. Moreover, it is found that TARCH and GARCH models give better forecasting performance than EGARCH and APARCH models. In forecasting performance, the model under normal distribution gives more accurate forecasting performance than non-normal densities and generalized error distributions clearly outperform the student-t densities in case of SSE.展开更多
Building energy modeling(BEM)has become increasingly used in building energy conservation research.Prototype building models are developed to represent the typical urban building characteristics of a specific building...Building energy modeling(BEM)has become increasingly used in building energy conservation research.Prototype building models are developed to represent the typical urban building characteristics of a specific building type,meteorological conditions,and construction year.This study included four residential buildings and 11 commercial buildings to represent nationwide building types in China.With consideration of five climate zones and different construction years corresponding to national standards,a total of 151 prototype building models were developed.The building envelope properties,occupancy and energy-related behaviors,and heating,ventilation,and air-conditioning(HVAC)system characteristics were defined according to the corresponding building energy efficiency design standards,HVAC design standards,and through other sources,such as questionnaire surveys,on-site measurements,and literature,which reflect the real situation of existing buildings in China.Based on the developed prototype buildings,a large database of 9225 models in 270 cities was further developed to facilitate users to simulate building energy in different cities.In conclusion,the developed prototype building models can represent realistic building characteristics and construction practices of the most common residential and commercial buildings in China,serving as an important foundation for BEM.The models can be used for analyses related to building energy conservation research on typical individual buildings,including energy-saving technologies,advanced controls,and new policies,and providing a reference for the development of building energy codes and standards.展开更多
This paper presents a new stock pricing model based on arithmetic Brown motion. The model overcomes the shortcomings of Gordon model completely. With the model investors can estimate the stock value of surplus compani...This paper presents a new stock pricing model based on arithmetic Brown motion. The model overcomes the shortcomings of Gordon model completely. With the model investors can estimate the stock value of surplus companies, deficit companies, zero increase companies and bankrupt companies in long term investment or in short term investment.展开更多
In recent years the use of Markov chain models to model stock price movement has received increased attention among researchers.Markov chain models combine the discrete movements of a binomial tree model while retaini...In recent years the use of Markov chain models to model stock price movement has received increased attention among researchers.Markov chain models combine the discrete movements of a binomial tree model while retaining the Markovian properties of Brownian motion,thus allowing the best properties of both of these models.In this paper,the authors consider a Markov chain model in which the underlying market is solely determined by a two-state Markov chain.Such a Markov chain model is strikingly simple and yet appears capable of capturing various market movements.By proper selection of parameters,the Markov chain model can produce sample paths that are very similar to.or very distinct from a classical Brownian motion,as the authors demonstrate in this paper.This paper studies the stock loan valuation,or the value of a loan in which a risky share of stock is used as collateral,under such a model.Dynamic programming equations in terms of variational inequalities are used to capture the dynamics of the problem.These equations are solved in closed-form.Explicit optimal solutions are obtained.Numerical examples are also reported to illustrate the results.展开更多
Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we ...Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we propose a Hybrid Channel Stock model that incorporates multiple features of basic stock data,K-line charts and technical indicator factors for predicting the closing price of a stock on day n+1.The model combines multiple aspects of data and uses a multi-channel structure including improved CNN-TW,bidirectional LSTM and Transformer network.First,we construct the multi-channel branches of the multi-faceted feature fusion input network model;second,in this paper,we will use the concatenate method to stitch the output of each branch as the input of the rest of the network;the last layer in the network is the fully connected layer,which combines the linear activation function regression to output the predicted prices.Finally,we conducted extensive experiments on the Dow 30,SSH 50 and CSI100 indices.The experimental results show that the Hybrid Channel Stock method has the best performance with the smallest MSE,RMSE,MAE and MAPE compared with existing models.in addition,the experiments on different trading days validate the stability and effectiveness of the model,providing an important reference for investors to make stock investment decisions.展开更多
文摘The United Nations Framework Convention on Climate Change （UNFCCC） requires reporting net carbon stock changes and anthropogenic greenhouse gas emissions, including those related to forests. This paper describes the status of carbon stocks in sub tropical forests of Pakistan. There are two major sub types in subtropical forests of Pakistan viz a viz Subtropical Chir Pine and Subtropical broadleaved forests. A network of sample plots was laid out in four selected site. Two sites were selected from sub tropical Chir Pine （Pinus roxburghii） forests and two from Subtropical broadleaved forests. Measurement and data acquisition protocols were developed specifically for the inventory car- ried out from 2005 to 2010. In total 261 plots （each of lha.） were established. Estimation of diameter, basal area, height, volume and biomass was carried out to estimate carbon stocks in each of the four carbon pools of above- and below-ground live biomass. Soil carbon stocks were also determined by doing soil sampling. In mature （-100 years old） pine forest stand at Ghoragali and Lehterar sites, a mean basal area of 30.38 and 26.11 m2.ha-1 represented mean volume of 243 and 197 m3·ha-1, respectively. The average biomass （t.ha-1） was 237 in Ghoragali site and 186 tha-1 in Lehterar site, which is equal to 128 and 100 t·ha-1 including soil C. However, on average basis both the forests have 114.5± 2.26 t.ha-1 of carbon stock which comprises of 92% in tree biomass and only 8% in the top soils. In mixed broadleaved evergreen forests a mean basal area （m2.ha-1）was 3.06 at Kherimurat with stem volume of 12.86 and 2.65 at Sohawa with stem volume of 11.40 m3.ha-1. The average upper and under storey biomass （t·ha-1） was 50.93 in Kherimurat site and 40.43 t.ha-1 in Sohawa site, which is equal to 31.18 and 24.36 t ·ha-1 including soil C stocks. This study provides a protocol monitoring biomass and carbon stocks and valuable baseline data for in Pakistan＇s managed and unmanaged sub-tropical forests.
基金The National Natural Science Foundation of China under contract No.NSFC31702343the Science Foundation of Shanghai under contract No.13ZR1419700+4 种基金the Innovation Program of Shanghai Municipal Education Commission under contract No.13YZ091the National High-tech R&D Program of China(863 Program)under contract No.2012AA092303the Funding Program for Outstanding Dissertations in Shanghai Ocean Universitythe Funding Scheme for Training Young Teachers in Shanghai Colleges and the Shanghai Leading Academic Discipline Project(Fisheries Discipline)Involvement of Chen Yong was supported by SHOU International Center for Marine Studies and Shanghai 1000 Talent Program
文摘The southern Patagonian stock（SPS） of Argentinian shortfin squid, Illex argentinus, is an economically important squid fishery in the Southwest Atlantic. Environmental conditions in the region play an important role in regulating the population dynamics of the I. argentinus population. This study develops an environmentally dependent surplus production（EDSP） model to evaluate the stock abundance of I. argentines during the period of 2000 to 2010. The environmental factors（favorable spawning habitat areas with sea surface temperature of 16–18°C） were assumed to be closely associated with carrying capacity（K） in the EDSP model. Deviance Information Criterion（DIC） values suggest that the estimated EDSP model with environmental factors fits the data better than a Schaefer surplus model without environmental factors under uniform and normal scenarios.The EDSP model estimated a maximum sustainable yield（MSY） from 351 600 t to 685 100 t and a biomass from 1 322 400 t to1 803 000 t. The fishing mortality coefficient of I. argentinus from 2000 to 2010 was smaller than the values of F（0.1） and F（MSY）. Furthermore, the time series biomass plot of I. argentinus from 2000 to 2010 shows that the biomass of I.argentinus and this fishery were in a good state and not presently experiencing overfishing. This study suggests that the environmental conditions of the habitat should be considered within squid stock assessment and management.
基金Under the auspices of Basic Project of State Commission of Science Technology of China(No.2008FY110600)National Natural Science Foundation of China(No.91325301,41401237,41571212,41371224)Field Frontier Program of Institute of Soil Science,Chinese Academy of Sciences(No.ISSASIP1624)
文摘The main aim of this paper was to calculate soil organic carbon stock(SOCS) with consideration of the pedogenetic horizons using expert knowledge and GIS-based methods in northeastern China.A novel prediction process was presented and was referred to as model-then-calculate with respect to the variable thicknesses of soil horizons(MCV).The model-then-calculate with fixed-thickness(MCF),soil profile statistics(SPS),pedological professional knowledge-based(PKB) and vegetation type-based(Veg) methods were carried out for comparison.With respect to the similar pedological information,nine common layers from topsoil to bedrock were grouped in the MCV.Validation results suggested that the MCV method generated better performance than the other methods considered.For the comparison of polygon based approaches,the Veg method generated better accuracy than both SPS and PKB,as limited soil data were incorporated.Additional prediction of the pedogenetic horizons within MCV benefitted the regional SOCS estimation and provided information for future soil classification and understanding of soil functions.The intermediate product,that is,horizon thickness maps were fluctuant enough and reflected many details in space.The linear mixed model indicated that mean annual air temperature(MAAT) was the most important predictor for the SOCS simulation.The minimal residual of the linear mixed models was achieved in the vegetation type-based model,whereas the maximal residual was fitted in the soil type-based model.About 95% of SOCS could be found in Argosols,Cambosols and Isohumosols.The largest SOCS was found in the croplands with vegetation of Triticum aestivum L.,Sorghum bicolor(L.) Moench,Glycine max(L.) Merr.,Zea mays L.and Setaria italica(L.) P.Beauv.
文摘On the basis of the analysis of classical stock model, according to the limitation of the model, the article puts forward the revision of classical model and enforces the applicability of the stock model.
文摘Through analyzing the desired characteristics of fittings in a nuclear power plant, the representative random stock models are built, and forecast methods about the desired probability of fittings are discussed secondly, the design of the plant fittings stock decision support system (FSDSS) is given. Then the main features of this system and function modules are introduced, and the special emphasis on organization of a database and composition and memory of a model base is given.
基金Supported by National Natural Science Foundation of China(11961005)Guangdong Province General University Characteristic Innovation Project(2018KTSCX253).
文摘This article attempted to construct a multi-factor quantitative stock selection model,analyze the financial indicators and transaction data of listed companies in detail via the big data statistical test method,and to find out the alpha excess return relative to the market in the case of short stock index futures as a hedge in the Chinese market.
文摘This paper examines the forecasting performance of different kinds of GARCH model （GRACH, EGARCH, TARCH and APARCH） under the Normal, Student-t and Generalized error distributional assumption. We compare the effect of different distributional assumption on the GARCH models. The data we analyze are the daily stocks indexes for Shenzhen Stock Exchange （SSE） in China from April 3^rd, 1991 to April 14^th, 2005. We find that improvements of the overall estimation are achieved when asymmetric GARCH models are used with student-t distribution and generalized error distribution. Moreover, it is found that TARCH and GARCH models give better forecasting performance than EGARCH and APARCH models. In forecasting performance, the model under normal distribution gives more accurate forecasting performance than non-normal densities and generalized error distributions clearly outperform the student-t densities in case of SSE.
基金supported by the National Natural Science Foundation of China (No.52108068)the Beijing Municipal Natural Science Foundation of China (No.8222019)the National Natural Science Foundation of China (No.52225801).
文摘Building energy modeling(BEM)has become increasingly used in building energy conservation research.Prototype building models are developed to represent the typical urban building characteristics of a specific building type,meteorological conditions,and construction year.This study included four residential buildings and 11 commercial buildings to represent nationwide building types in China.With consideration of five climate zones and different construction years corresponding to national standards,a total of 151 prototype building models were developed.The building envelope properties,occupancy and energy-related behaviors,and heating,ventilation,and air-conditioning(HVAC)system characteristics were defined according to the corresponding building energy efficiency design standards,HVAC design standards,and through other sources,such as questionnaire surveys,on-site measurements,and literature,which reflect the real situation of existing buildings in China.Based on the developed prototype buildings,a large database of 9225 models in 270 cities was further developed to facilitate users to simulate building energy in different cities.In conclusion,the developed prototype building models can represent realistic building characteristics and construction practices of the most common residential and commercial buildings in China,serving as an important foundation for BEM.The models can be used for analyses related to building energy conservation research on typical individual buildings,including energy-saving technologies,advanced controls,and new policies,and providing a reference for the development of building energy codes and standards.
文摘This paper presents a new stock pricing model based on arithmetic Brown motion. The model overcomes the shortcomings of Gordon model completely. With the model investors can estimate the stock value of surplus companies, deficit companies, zero increase companies and bankrupt companies in long term investment or in short term investment.
基金supported in part by the Simons Foundation(235179 to ZHANG Qing)
文摘In recent years the use of Markov chain models to model stock price movement has received increased attention among researchers.Markov chain models combine the discrete movements of a binomial tree model while retaining the Markovian properties of Brownian motion,thus allowing the best properties of both of these models.In this paper,the authors consider a Markov chain model in which the underlying market is solely determined by a two-state Markov chain.Such a Markov chain model is strikingly simple and yet appears capable of capturing various market movements.By proper selection of parameters,the Markov chain model can produce sample paths that are very similar to.or very distinct from a classical Brownian motion,as the authors demonstrate in this paper.This paper studies the stock loan valuation,or the value of a loan in which a risky share of stock is used as collateral,under such a model.Dynamic programming equations in terms of variational inequalities are used to capture the dynamics of the problem.These equations are solved in closed-form.Explicit optimal solutions are obtained.Numerical examples are also reported to illustrate the results.
基金supported by these three foundation programs:the Science and Technology Research Project(Youth)of Chongqing Municipal Education Commission(KJQN202201142)the Chongqing Research Program of Basic Research Frontier Technology(CSTB2022BSXM-JCX0069CCCC)the Training Program of the National Natural Science Foundation of China and National Social Science Fund of China of Chongqing University of Technology(2022PYZ030)。
文摘Stock market is volatile and predicting stock prices is a challenging task.Stock prices are influenced by multiple factors,and prediction using only numerical or image features is ineffective.To solve this problem,we propose a Hybrid Channel Stock model that incorporates multiple features of basic stock data,K-line charts and technical indicator factors for predicting the closing price of a stock on day n+1.The model combines multiple aspects of data and uses a multi-channel structure including improved CNN-TW,bidirectional LSTM and Transformer network.First,we construct the multi-channel branches of the multi-faceted feature fusion input network model;second,in this paper,we will use the concatenate method to stitch the output of each branch as the input of the rest of the network;the last layer in the network is the fully connected layer,which combines the linear activation function regression to output the predicted prices.Finally,we conducted extensive experiments on the Dow 30,SSH 50 and CSI100 indices.The experimental results show that the Hybrid Channel Stock method has the best performance with the smallest MSE,RMSE,MAE and MAPE compared with existing models.in addition,the experiments on different trading days validate the stability and effectiveness of the model,providing an important reference for investors to make stock investment decisions.
