نتایج جستجو برای: keywords artificial neural networks

تعداد نتایج: 2703519  

2004
P. Ramasubramanian

This paper describes a framework for a statistical anomaly prediction system using ensemble Quickprop neural network forecasting model, which predicts unauthorized invasions of user based on previous observations and takes further action before intrusion occurs. This paper focuses on detecting significant changes of transaction intensity for intrusion prevention. The experimental study is perfo...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه ارومیه - دانشکده فنی 1391

سرعت موج برشی (vs) در لایه های خاک یکی از مولفه های اساسی برای انجام محاسبات ژئوتکنیکی وتحلیل های دینامیکی به خصوص تعیین مدول برشی دینامیکی لایه های خاک می باشد. مقادیر سرعت موج برشی خاک توسط اندازه گیری مستقیم در صحرا از روش هایی ژئوفیزیکی و یا در آزمایشگاه از روش های ژئوتکنیکی به دست می آید. تعیین سرعت موج برشی خاک به روش های مذکور اگر چه دقیق می باشد ولی عموماً پر هزینه بوده و در برخی از پروژ...

دستورانی, محمدتقی, زرعی, محمدمهدی, عشقی زاده, مسعود, مصداقی, منصور,

Rainfall-runoff models are used in the field of hydrology and runoff estimation for many years, but despite existing numerous models, the regular release of new models shows that there is still not a model that can provide sophisticated estimations with high accuracy and performance. In order to achieve the best results, modeling and identification of factors affecting the output of the model i...

Journal: :international journal of industrial mathematics 2015
a. jafarian

‎artificial neural networks have the advantages such as learning, ‎adaptation‎, ‎fault-tolerance‎, ‎parallelism and generalization‎. ‎this ‎paper is a scrutiny on the application of diverse learning methods‎ ‎in speed of convergence in neural networks‎. ‎for this aim‎, ‎first we ‎introduce a perceptron method based on artificial neural networks‎ ‎which has been applied for solving a non-singula...

Time changes of return, inefficiency studies performed and presence of effective factors on share return rate are caused development modern and intelligent methods in estimation and evaluation of share return in stock companies. Aim of this research is prediction of return using financial variables with artificial neural network approach. Therefore, the statistical population of this study incl...

2016

parallel architectures for artificial neural networks paradigms and implementations systems PDF neural smithing supervised learning in feedforward artificial neural networks PDF artificial neural networks in biomedicine perspectives in neural computing PDF quantum neural computation intelligent systems control and automation science and engineering PDF foundations of neural networks fuzzy syste...

2011
Prasad Reddy

Software development effort prediction is one of the most key activities in software industry. Many models have been proposed to build a relationship between software size and effort; however we still have problems for effort prediction. This is because project data, available in the primary stages of project is often inadequate, unpredictable, uncertain and unclear. The need for accurate effor...

A.A. Aslaminejad A.R. Jafari Arvari M. Khojastehkey,

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

Journal: :journal of rehabilitation in civil engineering 2014
ali kheyroddin hosein naderpour masoud ahmadi

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

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