نتایج جستجو برای: شبکة عصبی lvq
تعداد نتایج: 16506 فیلتر نتایج به سال:
Article history: Received July 20, 2011 Accepted 7 October 2011 Available online 8 October 2011 The purpose of this paper is to predict the S&P500 down moves with technical analysis indicators using learning vector quantization (LVQ) neural networks and probabilistic neural networks (PNN). In addition, entropy-based input selection technique is employed to improve the prediction accuracies. The...
Prototype based models offer an intuitive interface to given data sets by means of an inspection of the model prototypes. Supervised classification can be achieved by popular techniques such as learning vector quantization (LVQ) and extensions derived from cost functions such as generalized LVQ (GLVQ) and robust soft LVQ (RSLVQ). These methods, however, are restricted to Euclidean vectors and t...
Brain magnetic resonance imaging (MRI) classification into normal and abnormal is a critical and challenging task. Owing to that, several medical imaging classification techniques have been devised in which Learning Vector Quantization (LVQ) is amongst the potential. The main goal of this paper is to enhance the performance of LVQ technique in order to gain higher accuracy detection for brain t...
Objective of this study is to investigate the potential of the learning vector quantizer neural network (LVQ-NN) classifier on various diagnostic variables used in the modern cytopathology laboratory and to build an algorithm that may facilitate the classification of individual cases. From all women included in the study, a liquid-based cytology sample was obtained; this was tested via HPV DNA ...
Learning vector quantization (LVQ) schemes constitute intuitive, powerful classification heuristics with numerous successful applications but, so far, limited theoretical background. We study LVQ rigorously within a simplifying model situation: two competing prototypes are trained from a sequence of examples drawn from a mixture of Gaussians. Concepts from statistical physics and the theory of ...
We apply Learning Vector Quantization (LVQ) in automated boar semen quality assessment. The classification of single boar sperm heads into healthy (normal) and non-normal ones is based on grey-scale microscopic images only. Sample data was classified by veterinary experts and is used for training a system with a number of prototypes for each class. We apply as training schemes Kohonen’s LVQ1 an...
In this paper, a new neural network paradigm and its application to recognition of speech patterns is presented. The novel NN paradigm is a multilayer version of the well-known LVQ algorithm from Kohonen. The approach includes the following innovations and improvements compared to other popular neural network paradigms: 1) It is according to the knowledge of the author the first multilayer vers...
روشها و الگوهای اقتصاد سنجی متفاوتی، از قبیل تجزیه و تحلیل رگرسیون و سریهای زمانی به منظور پیشبینی تقاضای آب، بهطور معمول توسط محققان مختلف مورد استفاده قرار گرفتهاند. اما در سالهای اخیر تکنیک جدید شبکههای عصبی به عنوان ابزاری مؤثر و کارا در پیشبینی متغیرهای اقتصادی مطرح شده است. در مقالة حاضر، از شبکة عصبی نوع gmdh مبتنی برالگوریتم ژنتیک، الگوهای ساختاری و همچنین سریهای زمانی، به منظ...
امروزه بخش مهمی از تقاضای جهانی گردشگری را گردشگری فرهنگی تشکیل میدهد. بهرغم غنا و تنوع فرهنگی سکونتگاههای روستایی کشور، این گردشگری رشد مناسبی در این نواحی ندارد. هدف پژوهش حاضر بررسی و تحلیل راهبردهای مطلوب توسعة گردشگری فرهنگی در نواحی روستایی شهرستان بینالود است. روش تحقیق توصیفیـ تحلیلی با ماهیتی کاربردیـ توسعهای است. جمعآوری اطلاعات بهشیوة اسنادی و میدانی انجام شده است. با استفاده...
We propose to use learning vector quantization (LVQ) in novelty detection where a few outliers exist in training data. The codebook update of original LVQ is modified and the scheme to determine a threshold for each codebook is proposed. Experimental results on artificial and real-world problems are quite promising.
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