نتایج جستجو برای: شبکه gmdh

تعداد نتایج: 35919  

2006

stable. The main results are: data normalization is fundamental to obtain better precision, the larger the number of data points, the lesser the error, the error decreases with the decreasing of noise level. The next step is to develop an Ipen nuclear research reactor model and apply the GMDH methodology to predict the reactor variables. This work is a part of a Monitoring and Diagnosis System ...

Journal: :Neural networks : the official journal of the International Neural Network Society 2003
Nikolay I. Nikolaev Hitoshi Iba

This paper presents a constructive approach to neural network modeling of polynomial harmonic functions. This is an approach to growing higher-order networks like these build by the multilayer GMDH algorithm using activation polynomials. Two contributions for enhancement of the neural network learning are offered: (1) extending the expressive power of the network representation with another com...

2005
N. Nariman-Zadeh A. Darvizeh A. Jamali A. Moeini

Genetic Algorithm (GA) is deployed for optimal design of configuration involved in GMDH-type neural networks which is used for modelling of centre deflection, hoop strain and thickness strain of explosive forming process. In this way, a new encoding scheme is presented to genetically design the generalized GMDH-type neural networks in which the connectivity configuration in such networks is not...

Journal: :Poultry science 2010
M Mottaghitalab A Faridi H Darmani-Kuhi J France H Ahmadi

Neural networks (NN) are a relatively new option to model growth in animal production systems. One self-organizing submodel of artificial NN is the group method of data handling (GMDH)-type NN. The use of such self-organizing networks has led to successful application of the GMDH algorithm over a broad range of areas in engineering, science, and economics. The present study aimed to apply the G...

Journal: :JCIT 2010
Chen Hong

Traffic flow forecasting, the core element of intelligent transportation system, plays an important role in traffic information services and traffic guidance. Since neural network prediction needs plenty of training samples, it cannot guarantee the real-timeness of traffic flow forecasting. In this paper, a GMDH network was constructed by self-organization, and the network was applied to traffi...

Journal: :Proceedings of the National Academy of Sciences of the United States of America 1990
C Gietl

The isolation and sequence of a cDNA clone encoding the complete glyoxysomal malate dehydrogenase [gMDH; (S)-malate:NAD+ oxidoreductase, EC 1.1.1.37] of watermelon cotyledons are presented. Partial cDNA clones were synthesized in a three part strategy, taking advantage of the polymerase chain reaction technology with oligonucleotides based on directly determined amino acid sequences. Subsequent...

Journal: :Proceedings of the National Academy of Sciences of the United States of America 1994
C Gietl K N Faber I J van der Klei M Veenhuis

We have studied the significance of the N-terminal presequence of watermelon (Citrullus vulgaris) glyoxysomal malate dehydrogenase [gMDH; (S)-malate:NAD+ oxidoreductase; EC 1.1.1.37] in microbody targeting. The yeast Hansenula polymorpha was used as heterologous host for the in vivo expression of various genetically altered watermelon MDH genes, whose protein products were localized by immunocy...

2002
Mark S. Voss Xin Feng

A new methodology for Emergent System Identification is proposed in this paper. The new method applies the self-organizing Group Method of Data Handling (GMDH) functional networks, Particle Swarm Optimization (PSO), and Genetic Programming (GP) that is effective in identifying complex dynamic systems. The focus of the paper will be on how Particle Swarm Optimization (PSO) is applied within Grou...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تربیت مدرس - دانشکده مدیریت و اقتصاد 1391

پیش بینی سود هر سهم و تغییرات آن به عنوان یک رویداد اقتصادی از دیر باز مورد علاقه سرمایه گذاران ، مدیران ، تحلیل گران مالی ، محققین و اعتبار دهندگان بوده است. این توجه ناشی از استفاده سود در مدل های ارزیابی سهام ، کمک به کارکرد کارای بازار سرمایه ( ارتباط مفروض بین تغییرات سود و تغییرات قیمت سهام )، ارزیابی توان پرداخت ( سود سهام، بهره و سایر تعهدات )، ارزیابی ریسک، ارزیابی عملکرد واحد اقتصادی ...

در این پژوهش از شبکه عصبی GMDH  مبتنی بر الگوریتم ژنتیک به عنوان ابزاری با قابلیت بالا در مدل‌سازی سیستم‌های غیرخطی پویای پیچیده، برای پیش‌بینی قیمت بنزین با دو روش قیاسی و قواعد تحلیل تکنیکی، استفاده کرده‌ایم. متغیرهای ورودی در روش قیاسی شامل تمام عوامل مؤثر(درون و برون سیستمی) بر قیمت بنزین و در روش تحلیل تکنیکی شامل میانگین‌های متحرک کوتاه و بلندمدت است. نتایج نشان­دهنده دقت بیش از 96درصد پی...

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