نتایج جستجو برای: artificial neuronal network
تعداد نتایج: 981848 فیلتر نتایج به سال:
Foraging is an embodied cognitive process which balances the search constraints of exploration versus exploitation. As such, foraging strategies and mechanisms offer useful insight into abstract forms of search such as visual search, problem solving, and semantic recall. We performed a series of simulations using artificial neural networks to relate metastable neuronal dynamics to observed fora...
We created a spiking neural controller for an agent that could use two different types of information encoding strategies depending on the level of chemical concentration present in the environment. The first goal of this research was to create a simulated agent that could react and stay within a region where there were two different overlapping chemicals having uniform concentrations. The agen...
We investigate rules that govern neuronal arborization, speci%cally the local geometry of the bifurcation of a neurite into its sub-branches. In the present study we set out to determine the relationship between branch diameter and angle. Existing theories are based on minimizing a neuronal volume cost function, or, alternatively, on the equilibrium of mechanical tension forces, which depend on...
Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fiel...
Introduction: Logistic regression is one of the modeling methods for bipartite dependent variables. On the other hand, artificial neural network is a flexible method with the least limitation. The importance of growing unnecessary beauty surgeries and the importance of prediction and classification made us consider the present study, with the aim of comparing logistic regression and artificial ...
The lack of sediment gauging stations in the process of wind erosion, caused of estimate of sediment be process of necessary and important. Artificial neural networks can be used as an efficient and effective of tool to estimate and simulate sediments. In this paper two model multi-layer perceptron neural networks and radial neural network was used to estimate the amount of sediment in Korsya o...
Introduction: It is of utmost importance to predict cardiovascular diseases correctly. Therefore, it is necessary to utilize those models with a minimum error rate and maximum reliability. This study aimed to combine an artificial neural network with the genetic algorithm to assess patients with myocardial infarction and congestive heart failure. Materials & Methods: This study utilized a m...
Background: Diabetes ever-increasing prevalence and the heavy burdens of controlling and treatment of the disease on people and the country have turned to be greatest challenges for governmental and healthcare authorities. Therefore, the disease prevention takes top priority and to do so the only possible way is detecting the effective parameters and controlling them. This study is about to for...
Introduction: Brucellosis is considered as one of the most important common infectious diseases between humans and animals. Considering the endemic nature of brucellosis and the existence of numerous reports of human and animal cases of brucellosis in Iran, the incidence of human brucellosis in Rafsanjan city was determined in the last 3 years (2016–2018). The main objective of this study was t...
Statistical analysis and forecast discharge data play an important role in management and development of water systems. The most fundamental issues of statistical analysis and forecast discharge in Iran are lack of data in long term period and lack of stream flow data in gauging stations. Considering the issues mentioned in this study, we tried to estimate the daily data flow (runoff) of Santeh...
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