Population projection for many developing countries like Bangladesh could be quite a challenging task. The objective of this paper is to compare between different types of population models and to find out the most suitable population models for long term population projection. We represented some population models such as Malthusian model, Logistic model, Gompertz model and Schaefer model to investigate their solution and plot their graphs. We predicted the human population of Bangladesh during 1980 to 2080 by applying both Malthusian and Logistic models using the actual population data of 1980 to 2013 from World Bank. The study reveals that short time population prediction is more accurate in Malthusian model. But in long term prediction, population growth is more unrealistic. But Logistic model is more realistic in long term prediction as compared to Malthusian model. Our work touched a little part of it.The realistic prediction of human population in future is very essential. We believe that extensive and continuous involvement in population dynamics research may result in to answer many questions and also may bring tremendous achievements for the next generation.
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Population projection for many developing countries like Bangladesh could be quite a challenging task. The objective of this paper is to compare between different types of population models and to find out the most suitable population models for long term population projection. We represented some population models such as Malthusian model, Logistic model, Gompertz model and Schaefer model to investigate their solution and plot their graphs. We predicted the human population of Bangladesh during 1980 to 2080 by applying both Malthusian and Logistic models using the actual population data of 1980 to 2013 from World Bank. The study reveals that short time population prediction is more accurate in Malthusian model. But in long term prediction, population growth is more unrealistic. But Logistic model is more realistic in long term prediction as compared to Malthusian model. Our work touched a little part of it.The realistic prediction of human population in future is very essential. We believe that extensive and continuous involvement in population dynamics research may result in to answer many questions and also may bring tremendous achievements for the next generation. 80 pp. Englisch. N° de réf. du vendeur 9783659715631
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Vendeur : moluna, Greven, Allemagne
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Asaduzzaman Md.As a student of Mathematics discipline in Khulna University, Bangladesh I proclaim that I am very much great-full to Almighty Allah and also thank to my honorable supervisor Dr.Md.Haider Ali Biswas for his proper guida. N° de réf. du vendeur 158961975
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Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Population projection for many developing countries like Bangladesh could be quite a challenging task. The objective of this paper is to compare between different types of population models and to find out the most suitable population models for long term population projection. We represented some population models such as Malthusian model, Logistic model, Gompertz model and Schaefer model to investigate their solution and plot their graphs. We predicted the human population of Bangladesh during 1980 to 2080 by applying both Malthusian and Logistic models using the actual population data of 1980 to 2013 from World Bank. The study reveals that short time population prediction is more accurate in Malthusian model. But in long term prediction, population growth is more unrealistic. But Logistic model is more realistic in long term prediction as compared to Malthusian model. Our work touched a little part of it.The realistic prediction of human population in future is very essential. We believe that extensive and continuous involvement in population dynamics research may result in to answer many questions and also may bring tremendous achievements for the next generation.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 80 pp. Englisch. N° de réf. du vendeur 9783659715631
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Population projection for many developing countries like Bangladesh could be quite a challenging task. The objective of this paper is to compare between different types of population models and to find out the most suitable population models for long term population projection. We represented some population models such as Malthusian model, Logistic model, Gompertz model and Schaefer model to investigate their solution and plot their graphs. We predicted the human population of Bangladesh during 1980 to 2080 by applying both Malthusian and Logistic models using the actual population data of 1980 to 2013 from World Bank. The study reveals that short time population prediction is more accurate in Malthusian model. But in long term prediction, population growth is more unrealistic. But Logistic model is more realistic in long term prediction as compared to Malthusian model. Our work touched a little part of it.The realistic prediction of human population in future is very essential. We believe that extensive and continuous involvement in population dynamics research may result in to answer many questions and also may bring tremendous achievements for the next generation. N° de réf. du vendeur 9783659715631
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Vendeur : preigu, Osnabrück, Allemagne
Taschenbuch. Etat : Neu. Comparative Studies and Predicting on Human Population in Bangladesh | Md. Asaduzzaman (u. a.) | Taschenbuch | 80 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659715631 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 104556795
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