Rapid prediction of optimum population size in genetic programming using a novel genotype -

2008 ◽  
Author(s):  
David C. Wedge ◽  
Douglas B. Kell
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Optimum Population ◽  
Rapid Prediction ◽  
Novel Genotype

Sustainable welfare and optimum population size

2015 ◽  
Vol 18 (6) ◽  
pp. 1679-1699 ◽  
Author(s):  
Theodore P. Lianos ◽  
Anastasia Pseiridis
Keyword(s):  
Population Size ◽  
Optimum Population

scholarly journals Optimum Population Size of Indigenous P-solubilizing Bacteria to Correct P Availability in Acid Soils

2013 ◽  
Vol 16 (1) ◽  
pp. 55-62
Author(s):  
. Sabaruddin ◽  
. Marsi ◽  
. Desti
Keyword(s):  
Population Size ◽  
Fresh Water ◽  
Acid Soils ◽  
Available P ◽  
P Availability ◽  
Optimum Population ◽  
Tidal Swamp ◽  
P Content ◽  
Initial Content

Indonesian acid soils were used to determine an optimum population size of indigenous P-solubilizing bacteria (PSB) for solubilizating fixed P. The experiment consisted of two sub-experiments. Sub-experiment I was to isolate the indigenous PSB from Ultisols, Fresh-water lowland Inceptisols, and tidal-swamp Inceptisols. Subexpriment II was to study the capacity of the isolated PSB to correct P availability in acid soils by inoculating the isolated PSB into the tested soils at 0, 105, 1010, and 1015 cells. The population of the indigenous PSB in the tested soils increased as a result of the inoculation. Both Al-P and Fe-P content in the three tested soils decreased as compared with the initial content. The increases of available P were significantly correlated with the decreases both in Al-P (r2 = 0.68 for the Ultisols; r2 = 0.51 for the fresh-water Inceptisols; and r2 = 0.35 for the tidal-swamp Inceptisols) and in Fe-P (r2 = 0.91 for the Ultisols; r2 = 0.45 for the fresh-water lowland Inceptisols; and r2 = 0.78 for the tidal-swamp Inceptisols). The increases of available P were significantly correlated with the increases of thepopulation of the PSB (r2 = 0.60 for the Ultisols; r2 = 0.55 for the fresh-water lowland Inceptisols; and r2 = 0.69 for the tidal-swamp Inceptisols). The available P in the three tested soils sharply increased if the population size of the PSB was about 1 × 109 cfu g-1 of soil.Keywords: Al-P, Fe-P, fresh-water lowland, isolated, Pikovskaya medium, tidal swamp

scholarly journals On sampling error in genetic programming

2021 ◽  
Author(s):  
Dirk Schweim ◽  
David Wittenberg ◽  
Franz Rothlauf
Keyword(s):  
Genetic Programming ◽  
Population Size ◽  
Sampling Error ◽  
Search Space ◽  
Initial Population ◽  
Frequency Model ◽  
Severe Problem ◽  
Large Populations ◽  
Population Sizes ◽  
Problem Instances

AbstractThe initial population in genetic programming (GP) should form a representative sample of all possible solutions (the search space). While large populations accurately approximate the distribution of possible solutions, small populations tend to incorporate a sampling error. This paper analyzes how the size of a GP population affects the sampling error and contributes to answering the question of how to size initial GP populations. First, we present a probabilistic model of the expected number of subtrees for GP populations initialized with full, grow, or ramped half-and-half. Second, based on our frequency model, we present a model that estimates the sampling error for a given GP population size. We validate our models empirically and show that, compared to smaller population sizes, our recommended population sizes largely reduce the sampling error of measured fitness values. Increasing the population sizes even more, however, does not considerably reduce the sampling error of fitness values. Last, we recommend population sizes for some widely used benchmark problem instances that result in a low sampling error. A low sampling error at initialization is necessary (but not sufficient) for a reliable search since lowering the sampling error means that the overall random variations in a random sample are reduced. Our results indicate that sampling error is a severe problem for GP, making large initial population sizes necessary to obtain a low sampling error. Our model allows practitioners of GP to determine a minimum initial population size so that the sampling error is lower than a threshold, given a confidence level.

scholarly journals Urban Optimum Population Size and Development Pattern Based on Ecological Footprint Model: Case of Zhoushan, China

2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Yuan LU
Keyword(s):  
Population Size ◽  
Urban Environment ◽  
Ecological Footprint ◽  
Natural Capital ◽  
Development Pattern ◽  
Optimum Population ◽  
Footprint Model ◽  
Ecological Resources ◽  
Optimal Population ◽  
The City

The agglomeration of population in the city can reflect the prosperity in the economy, society and culture. However, it has also brought a series of problems like environmental pollution, traffic congestion, housing shortage and jobs crisis. The results can be shown as the failure of urban comprehensive function, the decline of city benefits, and the contradiction between socioeconomic circumstance and ecosystem. Therefore, a reasonable population capacity, which is influenced by ecological resources, urban environment, geographical elements, social and economic factors, etc., is objectively needed. How to deal with the relationship between the utilization of natural capital and development of the city is extremely essential. This paper takes Zhoushan Island as an example, which is the fourth largest island off the coast of China. Firstly, the interactively influencing factors of urban optimal population are illustrated. And method is chosen to study the optimal population size. Secondly, based on the model of ecological footprint (EP), the paper calculates and analyzes the ecological footprint and ecological capacity of the Zhoushan Island, in order to explore the optimal population size of the city. Thirdly, analysis and evaluation of the resources and urban environment carrying capacity is made. Finally, the solution of the existing population problems and the suggestion for the future development pattern of the city are proposed in the urban eco-planning of Zhoushan Island. The main strategies can be summarized in two aspects: one is to reduce the ecological footprint, the other is to increase the ecological supply. The conclusion is that the current population of Zhoushan Island is far beyond the optimum population size calculated by the ecological footprint model. Therefore, sustainable development should be the guidance for urban planning in Zhoushan Island, and a low-carbon development pattern for the city is advocated.

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