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Urbanization moderate scale management of land and grain production based on evolutionary algorithm.

1. Introduction

Land is the foundation of human survival, is the most important agricultural production material, the protection and utilization of land for stability and improves agricultural productivity; ensure national food security is of great significance. With the accelerated process of urbanization in China, constantly improve the level of urbanization, in this process, land use pattern also constantly changing, land scale management level continuously improve is an important performance of this change. Although the scale management of land and food production between whether there is significant positive related academia is still controversial, however, the 18 big reports of the party clearly pointed out: to promote industrialization and urbanization of the coordination between the benign interaction, urbanization and agricultural modernization, and promote the simultaneous development of industrialization, informatization, urbanization, agricultural modernization. To speed up the development of modern agriculture, enhance the ability of comprehensive agricultural production, to ensure the effective supply of national food security and important agricultural products. Development of various forms of scale management, build intensive, professional, organized, and social integration of new agricultural business entities. Accelerate the construction of urbanization cannot be at the expense of food production, urbanization to protect food security as the foundation, always tighten the string of food security (Xu, 2011; Pereira, 2015). Heilongjiang Province is China's major grain producing area and an important commodity grain base, in-depth study of Heilongjiang Province to promote urbanization in the process of land scale management and food production, not only conducive to the promotion of Heilongjiang Province Rural Economic and social development and for the protection of national food security, maintenance of national economic and social stability is of important significance. Firstly, literature on domestic and foreign about urbanization and scale land management and food production to sort out, to find out the academic circles for the three relations reached a consensus and existing differences, secondly from theory on urbanization and scale land management and food production between internal mechanism, and then use statistical data in Heilongjiang Province of Heilongjiang Province urbanization and scale land management and food production by empirical analysis, and finally come to the conclusion put forward corresponding countermeasures and suggestions.

Domestic and foreign experts and scholars have conducted extensive research on the relationship between urbanization and land scale management. Hong (2005) believes that the greatest feature of urbanization is the agglomeration effect, the transfer of rural population is conducive to the land in the hands of farmers moderate concentration, to achieve the scale of agricultural operations and intensive management. In the long run, the development of urbanization is conducive to the protection of arable land, the reduction of agricultural population will help the development of agricultural scale management and improve the productivity of agriculture. Qu(2011) put forward urbanization to reduce the agricultural population, realize the scale, modern, intensive land management. A good, standard land circulation mechanism is the necessary condition to realize the land management of scale. Huang (1998) pointed out that with the advance of industrialization, urbanization and rural population transfer and the rural land contract and management rights gradually circulation and concentration. With the further transfer of the rural population, the rural circulation to undertake the management right of farmland area will continue to expand. From the existing literature, we can see that the relationship of urbanization and land scale operation, scholars draw a more consistent conclusion, consensus, that the urbanization process accelerated, urbanization rate continues to improve, conducive to the scale of operation of rural land, intensive management, contribute to the improvement of the efficiency of agricultural production, but the conduction of the relationship is the need for certain conditions.

There are many factors that affect grain production, and the research on the influence of land scale management on grain production has been studied extensively and deeply. At present, there are two kinds of views, a view that land scale management is able to overcome the adverse impact on food production of land, fragmentation, land scale management and grain production has a significant positive relationship; another view that China's grain production does not exist significant economies of scale, agricultural production is constant returns to scale characteristics. With the implementation of the rural household contract responsibility system, the enthusiasm of the farmers has been greatly improved, and the grain output has been greatly improved. Household management has also brought the land use of "fragmentation", the land fragmentation has negative impact on Grain Yield and statistically very significant (Zhang, 2010), reducing the farmers' grain production efficiency, reduced grain yield. Subsequently, the academic circles advocated the adoption of appropriate scale of land management to improve grain production. In Jiangsu province and Zhejiang Province on the scale of agricultural operations conducted an experimental investigation, found that large rice per unit yield higher than the village average of 8%, 3% higher than the wheat. Chen(2012) using the statistical data of Changshou City in Jiangsu Province, using production function and partial correlation analysis to draw the conclusion that the scale of cultivated land management has a significant positive effect on grain yield.

2. Evolutionary Algorithm

Evolutionary algorithm is based on Darwin's theory of evolution by simulating the process of biological evolution and mechanism of the problem of self--organization, adaptive artificial intelligence technology. Biological evolution is realized through reproduction, variation, competition and selection, and the evolutionary algorithm is mainly to solve the optimization problem by selecting, recombination and mutation of these three kinds of operations. Evolutionary computation is a kind of search algorithm based on natural selection and natural genetic mechanism. As the same with the ordinary search method, evolutionary computation is a kind of iterative algorithm; the different is evolutionary computation in the optimal solution search process, usually from a set of the original problem solution of improvement to another group of good solution, from the improved solution of further improvement. And in the evolution of the problem, when the optimization model of the original problem is established, the solution of the original problem must be coded. Evolutionary computation in the search process using structured and random information, so that the most satisfied with the goal of the decision to obtain the maximum survival possible, it is a probabilistic algorithm.


Generally speaking, evolutionary computation for solving includes following steps: given a set of initial solutions, the solutions of the performance evaluation; from the current this set of solutions in choose a certain number of solution as the basis for iterative solution; again on the operation, iterative solution; if these solutions satisfy the requirements then stop, otherwise will be obtained by the iterative solution as the current solution to operation.

Evolutionary computation includes 4 typical methods of genetic algorithm, genetic programming, evolutionary strategy and evolutionary programming. The first kind of method is more mature, and has been widely used. The application of evolutionary strategy and evolutionary programming in scientific research and practical problems is more and more widely. The main genetic operation of genetic algorithm are selection, crossover and mutation, and in the evolution rule and strategy, the evolution mechanism of source on selection and mutation. In terms of fitness, genetic algorithms are used to select a good parent, and evolutionary rules and evolutionary strategies are used to select offspring. Genetic algorithm and genetic programming emphasizes the parent offspring genetic chain, and rules of evolution and evolutionary strategy focuses on the sub generation behavior itself, immediately as a chain. Evolutionary rules and evolutionary strategies are generally not used to encode, eliminating the process of encoding and decoding procedures are more suitable for continuous optimization problems, but it cannot be non-numerical optimization. Evolutionary strategies can be used to determine the mechanisms that produce the parent generation for reproduction, and the genetic algorithm and evolutionary rules emphasize the dependence of individual fitness and probability. In addition, evolutionary rules are abstracted to the similarity between populations, and the evolutionary strategy is the similarity between individuals. Evolutionary strategies and evolutionary rules have been applied to many fields of continuous function optimization, pattern recognition, machine learning, neural network training, system identification and intelligent control.


3. Research method and variables

3.1. Method selection and variable

VAR model is often used to predict the time series system and analyze the dynamic impact of random disturbance on the variable system, so as to explain the impact of various economic shocks on the formation of economic variables. In this study, based on the test of the stability of the variables, the variables were analyzed by using VAR model and variance decomposition, to investigate the dynamic relationship between urbanization, land moderate scale management and grain production.

* Urbanization level (UR): Urbanization level is an important indicator to measure the level of urbanization in a country or region. Combined with the existing research, we found that there are 3 main methods to be used: (1) population index (2) land index method (3) urbanization index system method. In the three methods, more and more scholars use population index method, urban population accounted for accounted for the proportion of the total resident population and non-agricultural population household population proportion, the urban population accounted for the proportion of the total resident population to measure method of level of urbanization has been accepted by most scholars, and because data are easy to obtain, so this study by urbanization of the population accounts for the proportion of the total resident population to represent the level of urbanization.

* Moderate scale management of land (LS): The moderate scale management of land is a kind of management way that the operating cost is reduced gradually by expanding the area of land management. Existing index of land moderate scale management mainly include worth arable land, labor, the average cultivated land area and per capita cultivated land area. Based on the availability of data, this paper selects the rural household average per person to measure the index of cultivated land area to measure the degree of moderate scale management of land.

* Food production (CQ): The index of grain production has two indexes of total yield and per unit area yield. This paper selects the total grain output in this paper as a measure of grain production.

3.2. Data sources and descriptive statistics

This study selected in Heilongjiang Province from 1990 to 2011 years of sample data, all data sources in the calendar year "Heilongjiang statistical yearbook and the variables were log processing, calculation and analysis were in operation eviews 6.0 based. Since the 90's of last century, the urbanization process of Heilongjiang province has been accelerating, and the urbanization level has been continuously improved. 1990 Heilongjiang province urbanization rate of 48%, in 2011 the rate of urbanization increased to 56.5%, higher than the national level of 5.3 percentage points. At the same time, Heilongjiang Province, the average per capita operating area of cultivated land increased steadily, in 1990 for 7.46 acres, in to reach 10.42 acres in 2005 to reach 10 acres, in 2011 increased to 12.85 acres. In 1990 to 2011 years in Heilongjiang province's total grain yield except for individual years slight decline, the overall trend of rising trend, the grain production in 1990 for 2312.5 million tons, in 2008 exceeded 40 million tons, exceeded 500 million tons in 2010, reached 5012.8 million tons, become the country the second billions of pounds of production of province super. In 2011, Heilongjiang's grain output was more than a grain of grain, for the first time in Henan Province, which became the first province of grain production in the whole country.


4. Empirical analysis

4.1. Stability test

Due to the non-stationary time series analysis may produce spurious regression phenomenon. Therefore, the time series analysis requires the stationarity test and inspection methods are mainly ADF test and PP test methods. In this paper, the use of more extensive ADF test method for time series stability test, the specific test results as shown in table 1. As can be seen from the table 1, the time series LNUR, LNLS and LNCQ in 5% of the significant levels are non-stationary sequence, its first order difference after the three variables for a smooth sequence, that is, the first order of the entire sequence, denoted as I (1).

4.2. Co integration test

The purpose of co integration test is to determine whether there is a long-term equilibrium relationship between variables. In order to determine the model parameters has more explanatory power, must be to seek the balance between the lag period and the degree of freedom, this paper based on the LR test statistic, FPE, AIC information criterion, SC information criterion and HQ information criterion five indicators of lag order selection. Results are shown in Table 2. The results show that the selection of the 2 criteria in the late period of the 4 order delay, the selection of 3 criteria has 1, in order to meet the criteria for the selection criteria, we consider the model of the optimal lag order of 2 order.

The characteristics of the root of urbanization, land scale management and food production of three variables cointegration test. Test results are shown in table 3. From the cointegration test results, we found that in the absence of cointegration equation and at least a cointegration equation of the trace statistics at the 5% significance level rejected the null hypothesis, which shows that there exists a long-term co integration relationship between LNUR, lnls and LNCQ three variables that between 1990 to 2011 in Heilongjiang Province urbanization and scale land management and food production exist long-run equilibrium relationship.

4.3. Grainger causality test

The co integration test shows just there is a long-term equilibrium relationship between the urbanization and scale land management and food production, but the relationship is a causal relationship, still need further do Granger causality test. Test results are shown in table 4. The analysis of Grainger causality test results the following conclusions can be drawn: first, significant at the 10% level, the scale management of land grain production in LNLS is Grainger LNCQ, Grainger LNCQ is not a grain production scale land management LNLS, there is a one-way causal relationship between land scale management and food production LNLS LNCQ, which is the early information of land scale management LNLS will affect the current grain production of LNCQ; second, there is no causal relationship between Grainger and the grain production in town; third, at 5% level, urbanization causes the land scale management LNUR is Grainger LNLS, Grainger LNLS is not the scale management of land urbanization LNUR, with a one-way causal relationship between urbanization LNUR and LNLS scale land management.

4.4. Impulse response analysis

The impulse response is analyzed when an error term is changed, or when the model is subjected to a certain impact on the system dynamics. Figure 4 is the impulse response graphs on Heilongjiang Province urbanization and scale land management and food production, the horizontal axis of the graph represents the is impact lag periods and the vertical axis represents the impulse response variables, the dotted line is standard deviation band, the solid line shows the impulse response function. It shows urbanization of their own a standard difference of positive innovation, has the positive effect in the first period, followed by a substantial decline, in the fifth period before have the positive effects, but from the beginning of the fifth to the tenth stage has been negative impact. The urbanization on the land scale management positive new interest and a standard deviation, the influence of the first phase as 0, leveled off after reached the maximum in the third period, the overall positive influence. This shows that there is a long-term close relationship between land scale management and urbanization, land scale management has a positive role in promoting urbanization. The urbanization of grain production of a standard deviation of the positive new information, in the first phase of the impact as 0, in the third period reached the maximum after the decline, but the overall positive impact. This shows that there is a long-term close relationship between urbanization and food production, in the short term urbanization had a strong response to food production, from the long run this response is gradually weakened, but still has a stable and positive role in promoting.


Figure 5 shows that the scale of the land management of a standard deviation of the positive new information, in the first phase has a negative impact, followed by the negative impact of each period, and the negative impact of the gradual increase. Land scale management of their own a standard difference of positive innovation. In the first period has positive effect, began to exhibit wavy effect from the first stage, even down to a trough, the crest of odd period rise, the trough value and peak value is basically the same, on the whole is now positive effect. Land scale management on grain production in a standard deviation, effects in the first period of 0, second period has a small positive effect, third stage and after each period appear wavy effect, but are slightly negative effect.


Figure 6 shows that grain production of town of a standard positive innovation, has significantly positive effect in the first period, then declined gradually, starts from the fourth to the tenth period were negative effect, and the negative effect gradually increases. The grain production of land scale operation of a standard forward new information, in the first phase of the impact, in the second period to the lowest after a slight rise to tenth, a positive impact on the overall. The grain production of a standard deviation of their own, in the first phase has a significant impact, and then decreased to sixth for 0, followed by a negative impact on the tenth.


5. Conclusions

Based on the statistical data of Heilongjiang Province, this paper studies the relationship between urbanization and moderate scale management of land and grain production in province. Mainly obtains the following conclusions: (1) despite the urbanization rate, moderate large-scale management of land and grain production of non-stationary time series, but after the first order difference tends to be stable, using five information criterion to determine the optimal lag period 2 order. (2) Co-integration test shows that there is a long-term stable relationship between urbanization, land scale management and grain production. (3) Granger causality test results show that there is no Granger causality between urbanization and food production; there is a one-way causal relationship between urbanization and land scale operation, at 5% significant level, urbanization is Granger cause of appropriate scale of operation of land; land moderate scale management and food production is a one-way causal relationship also exists between, at the 10% level of significance, the appropriate scale operation of land is the Granger cause of grain production. (4) From the analysis of impulse response function curve, we can know that there is a positive effect of urbanization on grain production in the short term. Urbanization has a negative impact on the moderate scale management of the land; the moderate scale management of land has a strong positive impact. (5) The variance decomposition shows, urbanization is mainly affected by its volatility effect. This effect remained at more than 58%; grain yield mainly by its fluctuation effect, but the effect gradually weakened, in the four urbanization has a great influence on the grain yield; appropriate scale land is mainly affected by urbanization, overall, three effects of moderate scale management of land relatively stable.

This paper reveals that the urbanization, moderate scale management of land and food production is not isolated, in the future development strategy to correctly handle the relationship between the three. Based on the relationship between urbanization and grain production, we should steadily push forward the urbanization and ensure the national food security. Urbanization can promote the grain production in the short term, however, the promotion effect is gradually weakened, and the urbanization has a negative effect on grain production in the medium and long term. The reason may be in the short term the rural surplus labor transfer to urban and bring the improvement of the efficiency of grain production, with much of the labor force flow to urbanization, the improvement of grain yield influenced and restricted by the shortage of labor. Based on the positive pulling effect of moderate scale management of land and grain production, and actively promote the appropriate scale of land management, both to improve the level of urbanization, there can be to promote food production. Establishment and improve the land transfer system, cultivate the market of circulation of rural land contracted management right, land supply and demand information smooth and symmetrical, encourage landowners to the grower and business experts, implementation of grain production scale, intensive management.

Recebido/Submission: 07/03/2016

Aceitacao/Acceptance: 4/07/2016


The work of this paper is supported by Philosophy and Social Science Foundation of Heilongjiang Province (13C012); Applied technology and research and development program of Heilongjiang provincial science and Technology Department (GZ13D103).


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Tao Zhai, Yadong Fan

Northeast Agriculture University, Haerbin 150030, China
Table 1--Stationary test results of time series

time           type      ADF       5% critical   P value   conclusion
series                             value

LNUR           (C T 0)   -3.4416   -3.7105       0.0790    Not stable
LNLS           (C T 0)   -0.3210   -3.6584       0.9835    Not stable
LNCQ           (C T 0)   -1.4616   -3.6450       0.8103    Not stable
[DELTA]LNUR    (0 0 0)   -3.0697   -1.9591       0.0040    stable
[DELTA]LNLS    (C T 0)   -8.0953   -3.6585       0.0000    stable
[DELTA]LNCQ    (0 0 0)   -4.2391   -1.9591       0.0002    stable

Table 2--Selection results of lag order

Lag   LR           FPE          AIC          SC           HQ

0     NA           3.62e-08     -8.6201      -8.4714      -8.5953
1     63.64446     1.37e-09     -11.9161     -11.3196     -11.8151
2     17.57705 *   8.92e-10 *   -12.4335     -11.3896 *   -12.2568 *
3     9.114994     1.07e-09     -12.4989 *   -11.0077     -12.2465

Table 3--J-J cointegration test results

integration   characteristic   Trace       5% critical   P value
equation      value            statistic   value

None *        0.7349           44.0695     29.7971       0.0006
At most 1 *   0.5750           18.8468     15.4947       0.0150
At most 2     0.1275           2.5919      3.8415        0.1074

Table 4--Granger causality test results

hypothesis                          sample   F statistics

LNLS does not Granger Cause LNCQ    20       3.0037
LNCQ does not Granger Cause LNLS             1.1799
LNUR does not Granger Cause LNCQ    20       0.3701
LNCQ does not Granger Cause LNUR             2.0932
LNUR does not Granger Cause LNLS    20       4.9153
LNLS does not Granger Cause LNUR             2.0801

hypothesis                          P value  conclusion

LNLS does not Granger Cause LNCQ    0.0800   refuse
LNCQ does not Granger Cause LNLS    0.3343   Not refuse
LNUR does not Granger Cause LNCQ    0.6968   Not refuse
LNCQ does not Granger Cause LNUR    0.1578   Not refuse
LNUR does not Granger Cause LNLS    0.0228   refuse
LNLS does not Granger Cause LNUR    0.1595   Not refuse
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Author:Zhai, Tao; Fan, Yadong
Publication:RISTI (Revista Iberica de Sistemas e Tecnologias de Informacao)
Date:Jul 1, 2016
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