From the perspective of innovation mechanism,capital,personnel,achievements and conversion,this study analyzes the current situation of technological innovation in Beijing agricultural science and technology enterpris...From the perspective of innovation mechanism,capital,personnel,achievements and conversion,this study analyzes the current situation of technological innovation in Beijing agricultural science and technology enterprises,and summarizes the characteristics including single financing channel of R&D funds,low conversion rate of innovative products,unbalanced distribution of technology and innovative talents,the underestimated position of enterprises as the main body of technological innovation,the large gap of innovation achievements between developed provinces and Beijing.At last,this study puts forward the ways to improve technological innovation ability in Beijing agricultural science and technology enterprises as follows:developing technological innovation strategies;improving the R&D expenditure and expanding the financing channels;perfecting the mechanism of professional personnel training in agricultural technology innovation;enhancing the level of innovation performance management;establishing and improving the corporate culture of innovation and cultivating technology innovation spirit.展开更多
Based on the development of the non-governmental enterprises of science and technology in the past twenty years, this paper applied an interpretive structure model (ISM) to make a research on the regular development p...Based on the development of the non-governmental enterprises of science and technology in the past twenty years, this paper applied an interpretive structure model (ISM) to make a research on the regular development pattern of these enterprises and to probe into the interior development mechanism theoretically. The studying results supply ideas underlying the scientific decision for the governments at all levels and show the direction of the development of the non-governmental enterprises of science and technology in the future.展开更多
Chinese Academy Of Agricultural MechanizationSciences(CAAMS)is the largest research organizationwith the strongest innovation ability engaged infundamental,application sciences with multiple disciplines,comprehensiven...Chinese Academy Of Agricultural MechanizationSciences(CAAMS)is the largest research organizationwith the strongest innovation ability engaged infundamental,application sciences with multiple disciplines,comprehensiveness and gives priority to R&D on modernagriculture equipment while facing the needs of agriculture,countryside and farmers.Since the establishment of CAAMS40 years ago,it coordinated the related Ministries andCommissions of our country to finish researching andmanufacturing over 3000 kinds of agricultural machineries of9 categories,gained more than 2000 scientific and展开更多
Coal occupies a dominant position in China's national economy and is an essential energy source for future industrial development.To inform the efficient and sustainable development of the coal industry,this paper...Coal occupies a dominant position in China's national economy and is an essential energy source for future industrial development.To inform the efficient and sustainable development of the coal industry,this paper analyzes the sources of strategic risk for coal science and technology enterprises using 3 firstclass indicators,10 second-level indicators,and 37 observation points established through the existing research literature and experience.Moreover,in accordance to the obtained initial index data,the selected indicators have been tested and screened using reliability and membership degree analyses to remove redundant variables,avoid juxtaposition of risk factors at different levels,and reduce the influence of some tiny risk factors for enterprise strategic risk.Then,factor analysis of external environment factor sub-scale was carried out.Factors are extracted according to a standard characteristic value greater than 1.Variables with high coefficients are classified into one factor category;and finally,3 first-class indicators,8 second-level indicators,and 37 observation points are reconstructed.展开更多
In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integr...In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integrates the conventions of econometrics with the technological elements of data science.It make use of machine learning(ML),predictive and prescriptive analytics to effectively understand financial data and solve related problems.Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations.At the same time,it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis.AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems.With this motivation,this paper presents a new AI based optimal functional link neural network(FLNN)based financial crisis prediction(FCP)model forSMEs.The proposed model involves preprocessing,feature selection,classification,and parameter tuning.At the initial stage,the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data.Besides,a novel chaotic grasshopper optimization algorithm(CGOA)based feature selection technique is applied for the optimal selection of features.Moreover,functional link neural network(FLNN)model is employed for the classification of the feature reduced data.Finally,the efficiency of theFLNNmodel can be improvised by the use of cat swarm optimizer(CSO)algorithm.A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model.The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%,92.100%,and 95.220%on the applied Polish dataset Year I-III respectively.展开更多
基金Supported by Beijing Natural Science Foundation(9122006)Beijing Social Science Foundation(13JGB041)
文摘From the perspective of innovation mechanism,capital,personnel,achievements and conversion,this study analyzes the current situation of technological innovation in Beijing agricultural science and technology enterprises,and summarizes the characteristics including single financing channel of R&D funds,low conversion rate of innovative products,unbalanced distribution of technology and innovative talents,the underestimated position of enterprises as the main body of technological innovation,the large gap of innovation achievements between developed provinces and Beijing.At last,this study puts forward the ways to improve technological innovation ability in Beijing agricultural science and technology enterprises as follows:developing technological innovation strategies;improving the R&D expenditure and expanding the financing channels;perfecting the mechanism of professional personnel training in agricultural technology innovation;enhancing the level of innovation performance management;establishing and improving the corporate culture of innovation and cultivating technology innovation spirit.
文摘Based on the development of the non-governmental enterprises of science and technology in the past twenty years, this paper applied an interpretive structure model (ISM) to make a research on the regular development pattern of these enterprises and to probe into the interior development mechanism theoretically. The studying results supply ideas underlying the scientific decision for the governments at all levels and show the direction of the development of the non-governmental enterprises of science and technology in the future.
文摘Chinese Academy Of Agricultural MechanizationSciences(CAAMS)is the largest research organizationwith the strongest innovation ability engaged infundamental,application sciences with multiple disciplines,comprehensiveness and gives priority to R&D on modernagriculture equipment while facing the needs of agriculture,countryside and farmers.Since the establishment of CAAMS40 years ago,it coordinated the related Ministries andCommissions of our country to finish researching andmanufacturing over 3000 kinds of agricultural machineries of9 categories,gained more than 2000 scientific and
文摘Coal occupies a dominant position in China's national economy and is an essential energy source for future industrial development.To inform the efficient and sustainable development of the coal industry,this paper analyzes the sources of strategic risk for coal science and technology enterprises using 3 firstclass indicators,10 second-level indicators,and 37 observation points established through the existing research literature and experience.Moreover,in accordance to the obtained initial index data,the selected indicators have been tested and screened using reliability and membership degree analyses to remove redundant variables,avoid juxtaposition of risk factors at different levels,and reduce the influence of some tiny risk factors for enterprise strategic risk.Then,factor analysis of external environment factor sub-scale was carried out.Factors are extracted according to a standard characteristic value greater than 1.Variables with high coefficients are classified into one factor category;and finally,3 first-class indicators,8 second-level indicators,and 37 observation points are reconstructed.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work under Grant Number(RGP 1/147/42),www.kku.edu.sa.This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-Track Path of Research Funding Program.
文摘In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integrates the conventions of econometrics with the technological elements of data science.It make use of machine learning(ML),predictive and prescriptive analytics to effectively understand financial data and solve related problems.Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations.At the same time,it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis.AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems.With this motivation,this paper presents a new AI based optimal functional link neural network(FLNN)based financial crisis prediction(FCP)model forSMEs.The proposed model involves preprocessing,feature selection,classification,and parameter tuning.At the initial stage,the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data.Besides,a novel chaotic grasshopper optimization algorithm(CGOA)based feature selection technique is applied for the optimal selection of features.Moreover,functional link neural network(FLNN)model is employed for the classification of the feature reduced data.Finally,the efficiency of theFLNNmodel can be improvised by the use of cat swarm optimizer(CSO)algorithm.A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model.The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%,92.100%,and 95.220%on the applied Polish dataset Year I-III respectively.
