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Predictive Mathematical and Statistical Modeling of the Dynamic Poverty Problem in Burundi: Case of an Innovative Economic Optimization System
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作者 Fulgence Nahayo Ancille Bagorizamba +1 位作者 Marc Bigirimana Irene Irakoze 《Open Journal of Optimization》 2021年第4期101-125,共25页
The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dyn... The mathematical and statistical modeling of the problem of poverty is a major challenge given Burundi’s economic development. Innovative economic optimization systems are widely needed to face the problem of the dynamic of the poverty in Burundi. The Burundian economy shows an inflation rate of -1.5% in 2018 for the Gross Domestic Product growth real rate of 2.8% in 2016. In this research, the aim is to find a model that contributes to solving the problem of poverty in Burundi. The results of this research fill the knowledge gap in the modeling and optimization of the Burundian economic system. The aim of this model is to solve an optimization problem combining the variables of production, consumption, budget, human resources and available raw materials. Scientific modeling and optimal solving of the poverty problem show the tools for measuring poverty rate and determining various countries’ poverty levels when considering advanced knowledge. In addition, investigating the aspects of poverty will properly orient development aid to developing countries and thus, achieve their objectives of growth and the fight against poverty. This paper provides a new and innovative framework for global scientific research regarding the multiple facets of this problem. An estimate of the poverty rate allows good progress with the theory and optimization methods in measuring the poverty rate and achieving sustainable development goals. By comparing the annual food production and the required annual consumption, there is an imbalance between different types of food. Proteins, minerals and vitamins produced in Burundi are sufficient when considering their consumption as required by the entire Burundian population. This positive contribution for the latter comes from the fact that some cows, goats, fishes, ···, slaughtered in Burundi come from neighboring countries. Real production remains in deficit. The lipids, acids, calcium, fibers and carbohydrates produced in Burundi are insufficient for consumption. This negative contribution proves a Burundian food deficit. It is a decision-making indicator for the design and updating of agricultural policy and implementation programs as well as projects. Investment and economic growth are only possible when food security is mastered. The capital allocated to food investment must be revised upwards. Demographic control is also a relevant indicator to push forward Burundi among the emerging countries in 2040. Meanwhile, better understanding of the determinants of poverty by taking cultural and organizational aspects into account guides managers for poverty reduction projects and programs. 展开更多
关键词 Poverty Problem Mathematical Modeling applied statistics Operational Research Symplectic Partitioned Runge Kutta Algorithm Dynamic Programming Matlab and Simulink AMPL KNITRO Gurobi Economic Optimization Technology Transfer Incubation of Results Sustainable Development Goals
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Founding of the Big Data Statistics Branch
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作者 Shanping Wang 《Statistical Theory and Related Fields》 2019年第1期85-88,共4页
The founding conference of the Big Data Statistics Branch (BDSB) of the Chinese Association forApplied Statistics (CAAS) was held on 8 December 2018, at East China Normal University (ECNU),Shanghai, China. More than 6... The founding conference of the Big Data Statistics Branch (BDSB) of the Chinese Association forApplied Statistics (CAAS) was held on 8 December 2018, at East China Normal University (ECNU),Shanghai, China. More than 600 experts and scholars attended the conference. Professor ZhangRiquan was elected as the chairman of the first Board of Directors of the BDSB. Fang Xiangzhong,Chairman of the CAAS, delivered a speech. Professor Wang Zhaojun and Dr Liu Zhong delivered,respectively, keynote reports on the development of Big Data researches and practices, at theconference. The BDSB will be dedicated to building a high-level big data statistics exchange platform for experts and scholars in universities, governments, enterprises, and other fields to betterserve the society and serve the country’s major strategies. 展开更多
关键词 Big data Big Data statistics Branch Chinese Association for applied statistics FOUNDATION East China Normal University
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