The crop intensification program（CIP）was introduced in Rwanda in 2007 by the Ministry of Agriculture and Animal Resources（MINAGRI）,Rwanda,as a solution to the land fragmentation,low use of agricultural inputs and ...The crop intensification program（CIP）was introduced in Rwanda in 2007 by the Ministry of Agriculture and Animal Resources（MINAGRI）,Rwanda,as a solution to the land fragmentation,low use of agricultural inputs and low access to extension services.However,due to the voluntary nature of farmers’participation and their reluctance to participate,this study aimed at assessing the factors that influence their participation.Data were collected from 340 respondents through a household survey in Mayange and Rusarabuye sectors.Descriptive statistics and binary logistic regression model were used to analyze the data.Results show that the factors that significantly influenced the farmers’participation in the CIP include gender,non-farm income,farmland size,farming experience,land acquisition means,market access,trust and agro-ecological conditions.In fact,the non-farm income significantly increased the farmers’decisions to participate in the CIP（P〈0.001）as it eases the financial capital needed to invest in the CIP activities.On the land acquisition means,the farmers who inherited or bought the land positively and significantly participated in the CIP（P〈0.05）because they had the land tenure security.However,the participation in the CIP was hindered by inadequate irrigation and mechanization facilities,lack of farmers’participation in the CIP planning process,inadequate extension services,inadequate agricultural inputs and inadequate post-harvest technologies.Closer collaboration between farmers,local leaders,extension agents and agricultural service providers as well as the farmers’practical skills in irrigation and mechanization could enhance the participation to the program.Therefore,there is a need on the part of policymakers to empower farmers with adequate knowledge on better cropping practices and agricultural technologies through appropriate extension services and bottom-up based program.展开更多
Combining the statistic data of 1997~2009,this paper analyzes the income of farmers in eight minority areas, structure of consumption demand, the marginal propensity to consume and its constraints factors on eight min...Combining the statistic data of 1997~2009,this paper analyzes the income of farmers in eight minority areas, structure of consumption demand, the marginal propensity to consume and its constraints factors on eight minority provinces,finally, concludes with some specific proposals. That includes increasing peasant’s income, strengthening rural infrastructure construction, establishing perfect rural social security system and promoting reasonable and healthy consumption of peasants.展开更多
From the perspective of the influence on credit for farmers,this paper takes the temporarily poor farmers in Rongchang County of Chongqing Municipality as the respondents,and employs the expert survey method and on-si...From the perspective of the influence on credit for farmers,this paper takes the temporarily poor farmers in Rongchang County of Chongqing Municipality as the respondents,and employs the expert survey method and on-site analysis to analyze the reasons and put forward three hypotheses. Using the AHP model,we carry out the empirical analysis of three major hypotheses concerning the credit for farmers. The study demonstrates that the state's unclear definition of property rights of farmers and farmers' lack of collateral are the primary factor influencing the credit for farmers,followed by insufficient targeted financial and technical support for the farmers who are engaged in the agricultural sector affected by the nature; farmers do not really get the assistance for them to use the natural resources to develop the rural economy,so that the banks complicate the loan procedures and increase the requirements of loans for farmers in order to ensure the capital liquidity and safety,thus further deepening the plight of credit for farmers.展开更多
There are some adjustable parameters which directly influence the performance and stability of Particle Swarm Optimization algorithm. In this paper, stabilities of PSO with constant parameters and time-varying paramet...There are some adjustable parameters which directly influence the performance and stability of Particle Swarm Optimization algorithm. In this paper, stabilities of PSO with constant parameters and time-varying parameters are analyzed without Lipschitz constraint. Necessary and sufficient stability conditions for acceleration factor P and inertia weight w are presented. Experiments on benchmark functions show the good performance of PSO satisfying the stability condition, even without Lipschitz constraint. And the inertia weight ω value is enhanced to (-1,1). Keywords Lipschitz constraint - Time-varying discrete system - Adaptive acceleration factor - Stability展开更多
Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data. NMF has ap...Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data. NMF has applications in image processing, text mining, recommendation systems and a variety of other fields. Since its inception, the NMF algorithm has been modified and explored by numerous authors. One such modification involves the addition of auxiliary constraints to the objective function of the factorization. The purpose of these auxiliary constraints is to impose task-specific penalties or restrictions on the objective function. Though many auxiliary constraints have been studied, none have made use of data-dependent penalties. In this paper, we propose Zellner nonnegative matrix factorization (ZNMF), which uses data-dependent auxiliary constraints. We assess the facial recognition performance of the ZNMF algorithm and several other well-known constrained NMF algorithms using the Cambridge ORL database.展开更多
构网型储能设备(grid-forming energy storage system,GFM-ESS)因具备主动构网和提供惯量支持等能力,已成为解决大规模新能源接入引发宽频振荡问题的重要手段。然而,GFM-ESS的容量配置直接影响系统投资成本,在保障系统稳定性的前提下如...构网型储能设备(grid-forming energy storage system,GFM-ESS)因具备主动构网和提供惯量支持等能力,已成为解决大规模新能源接入引发宽频振荡问题的重要手段。然而,GFM-ESS的容量配置直接影响系统投资成本,在保障系统稳定性的前提下如何实现其经济性配置,成为当前研究热点。现有研究多侧重于提升系统稳定裕度,较少考虑GFM-ESS容量与选址的协同优化,且缺乏统一的量化指标指导配置方案的制定。为此,本工作基于s域模态分析理论,构建了一条集模态识别、关键节点筛选与容量协同优化于一体的完整技术链条,并提出一种考虑经济性约束的GFM-ESS容量与选址协同优化方法。首先,通过归一化模态参与因子对各母线的振荡模态贡献进行定量评估,识别影响不稳定模态的关键节点;针对系统多模态振荡特性,引入粒子群优化(particle swarm optimization,PSO)算法,在预选节点上对储能容量进行协同优化,以满足预设的稳定裕度指标。仿真结果表明,所提技术链能够有效识别关键控制节点,并以较小的GFM-ESS投入容量将原本不稳定的系统恢复至稳定状态,且具备明确的稳定裕度,为新型电力系统中GFM-ESS的合理配置提供了理论支撑。展开更多
基金The Institute of Resources, Ecosystem and Environment of Agriculture (IREEA) at Nanjing Agricultural University,Chinathe Chinese Scholarship Council (CSC) are thanked for the financial support
文摘The crop intensification program（CIP）was introduced in Rwanda in 2007 by the Ministry of Agriculture and Animal Resources（MINAGRI）,Rwanda,as a solution to the land fragmentation,low use of agricultural inputs and low access to extension services.However,due to the voluntary nature of farmers’participation and their reluctance to participate,this study aimed at assessing the factors that influence their participation.Data were collected from 340 respondents through a household survey in Mayange and Rusarabuye sectors.Descriptive statistics and binary logistic regression model were used to analyze the data.Results show that the factors that significantly influenced the farmers’participation in the CIP include gender,non-farm income,farmland size,farming experience,land acquisition means,market access,trust and agro-ecological conditions.In fact,the non-farm income significantly increased the farmers’decisions to participate in the CIP（P〈0.001）as it eases the financial capital needed to invest in the CIP activities.On the land acquisition means,the farmers who inherited or bought the land positively and significantly participated in the CIP（P〈0.05）because they had the land tenure security.However,the participation in the CIP was hindered by inadequate irrigation and mechanization facilities,lack of farmers’participation in the CIP planning process,inadequate extension services,inadequate agricultural inputs and inadequate post-harvest technologies.Closer collaboration between farmers,local leaders,extension agents and agricultural service providers as well as the farmers’practical skills in irrigation and mechanization could enhance the participation to the program.Therefore,there is a need on the part of policymakers to empower farmers with adequate knowledge on better cropping practices and agricultural technologies through appropriate extension services and bottom-up based program.
基金Support by National Social Science Fund Major Bidding Project in 2009-Research on Some Major Issues of Pushing Integrated Development of Economy and Society in Minority Areas under the New Situation(09&ZD011)
文摘Combining the statistic data of 1997~2009,this paper analyzes the income of farmers in eight minority areas, structure of consumption demand, the marginal propensity to consume and its constraints factors on eight minority provinces,finally, concludes with some specific proposals. That includes increasing peasant’s income, strengthening rural infrastructure construction, establishing perfect rural social security system and promoting reasonable and healthy consumption of peasants.
基金Supported by Business Management Cultivation Discipline of Rongchang Campus of Southwest University(RCQG207001)
文摘From the perspective of the influence on credit for farmers,this paper takes the temporarily poor farmers in Rongchang County of Chongqing Municipality as the respondents,and employs the expert survey method and on-site analysis to analyze the reasons and put forward three hypotheses. Using the AHP model,we carry out the empirical analysis of three major hypotheses concerning the credit for farmers. The study demonstrates that the state's unclear definition of property rights of farmers and farmers' lack of collateral are the primary factor influencing the credit for farmers,followed by insufficient targeted financial and technical support for the farmers who are engaged in the agricultural sector affected by the nature; farmers do not really get the assistance for them to use the natural resources to develop the rural economy,so that the banks complicate the loan procedures and increase the requirements of loans for farmers in order to ensure the capital liquidity and safety,thus further deepening the plight of credit for farmers.
文摘There are some adjustable parameters which directly influence the performance and stability of Particle Swarm Optimization algorithm. In this paper, stabilities of PSO with constant parameters and time-varying parameters are analyzed without Lipschitz constraint. Necessary and sufficient stability conditions for acceleration factor P and inertia weight w are presented. Experiments on benchmark functions show the good performance of PSO satisfying the stability condition, even without Lipschitz constraint. And the inertia weight ω value is enhanced to (-1,1). Keywords Lipschitz constraint - Time-varying discrete system - Adaptive acceleration factor - Stability
文摘Nonnegative matrix factorization (NMF) is a relatively new unsupervised learning algorithm that decomposes a nonnegative data matrix into a parts-based, lower dimensional, linear representation of the data. NMF has applications in image processing, text mining, recommendation systems and a variety of other fields. Since its inception, the NMF algorithm has been modified and explored by numerous authors. One such modification involves the addition of auxiliary constraints to the objective function of the factorization. The purpose of these auxiliary constraints is to impose task-specific penalties or restrictions on the objective function. Though many auxiliary constraints have been studied, none have made use of data-dependent penalties. In this paper, we propose Zellner nonnegative matrix factorization (ZNMF), which uses data-dependent auxiliary constraints. We assess the facial recognition performance of the ZNMF algorithm and several other well-known constrained NMF algorithms using the Cambridge ORL database.
