دانلود مقاله ISI انگلیسی شماره 49227
عنوان فارسی مقاله

طبقه بندی پیشرفت کشور به سوی یک اقتصاد دانش مبتنی بر تکنیک های طبقه بندی یادگیری ماشین

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
49227 2015 11 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Classification of countries’ progress toward a knowledge economy based on machine learning classification techniques
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, Volume 42, Issue 1, January 2015, Pages 562–572

کلمات کلیدی
سیستم های پشتیبانی تصمیم - فراگیری ماشین - اقتصاد دانش - خوشه بندی سلسله مراتبی - طبقه بندی ترتیبی
پیش نمایش مقاله
پیش نمایش مقاله طبقه بندی پیشرفت کشور به سوی یک اقتصاد دانش مبتنی بر تکنیک های طبقه بندی یادگیری ماشین

چکیده انگلیسی

Knowledge is a key factor of competitive advantages in the current economic crisis and uncertain environment. There are a number of indicators to measure knowledge advances, however, the benefits for stakeholders and policy makers are limited because of a lack of classification models. This paper introduces an approach to classify 54 countries (in 2007–2009) according to their progress toward a knowledge economy (KE). To achieve this, the aims of this paper are twofold: first, to find clusters of countries at a similar stage of development toward KE to test if they are meaningful; hence, it will be possible to order the clusters from early KEs (last cluster) to advanced KEs (first cluster). Second, having obtained these clusters, it is possible to build various models to detect the advancement of countries toward KE from one year to another due to its classification. Then, three ordinal classifiers from the machine-learning field were compared in order to select the classifier that performs the best and to confirm the ordinal description of the clusters. Finally, an ordinal model based on the Support Vector Ordinal Regression with Implicit Constraints was selected because of its ability to classify the patterns into the clusters, confirming the appropriateness of the clusters and their ordinal nature. The proposed ordinal classifier could be used for monitoring the progress or stage of transition to KE and for analysing whether a country changes clusters, entering one that performs better or worse.

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پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.