Artificial neural networks can predict multilayer perceptron networks. Medical search. Frequent questions

It was derived from the Bayesian network and a statistical algorithm called Kernel Fisher discriminant analysis. (wikipedia.org)
In current investigation, a novel implementation of intelligent numerical computing solver based on multi-layer perceptron (MLP) feed-forward back-propagation artificial neural networks (ANN) with the Levenberg-Marquard algorithm is provided to interpret heat generation/absorption and radiation phenomenon in unsteady electrically conducting Williamson liquid flow along porous stretching surface. (uaeu.ac.ae)
An efficient neural networks based genetic algorithm model for soil temperature prediction. (ac.ir)
Soil Temperature Estimation Based on Climatic Parameters Using Artificial Neural Network Models and Hybrid Firefly Algorithm (Case Study, East Azarbaijan Province). (ac.ir)
The ANN was optimized once by genetic algorithm (GA) and once again by particle swarm optimization algorithm (PSO) in order to predict the refractive index of binary solutions. (ac.ir)
Prediction of solubility of CO 2 in ethanol-[EMIM][Tf 2 N] ionic liquid mixtures using artificial neural networks based on genetic algorithm. (irost.ir)
An efficient gradient based network training algorithm has been employed to minimize the network training errors. (peacta.org)
For evaluation of suitable model for predicting seepage values (results of modeling), used from five artificial intelligence techniques comprising: multilayer perceptron neural network (MLP), radial base function (RBF), gene expression programming (GEP), support vector regression (SVR) and a novel hybrid model of the firefly algorithm (FFA) with the multilayer perceptron (MLP-FFA). (ac.ir)
The prediction model was built using a Multilayer perceptron (MLP) algorithm as part of the ANN with 10-fold cross-validation. (tmu.edu.tw)
A neural network is a machine learning algorithm that is used to model complex patterns in data. (inaya.cloud)
However, neural networks are a type of algorithm that's capable of learning. (inaya.cloud)
M. F. Mø ller, ``A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning'', Neural Networks 6 , 525 (1993). (lu.se)
C. Peterson and E. Hartman, ``Explorations of the Mean Field Theory Learning Algorithm'', Neural Networks 2 , 475 (1989). (lu.se)
Despite the fact that SOMs are a class of artificial neural networks, they are radically different from the neural model usually employed in Business and Economics studies, the multilayer perceptron with backpropagation training algorithm. (bvsalud.org)

A convolutional neural network (CNN, or ConvNet or shift invariant or space invariant) is a class of deep network, composed of one or more convolutional layers with fully connected layers (matching those in typical ANNs) on top. (wikipedia.org)
During recent years, statistical models based on artificial neural networks (ANNs) have been increasingly applied and evaluated for forecasting of air quality. (springer.com)
Overall high correlations between ground truth and predicted kinematic and kinetic data were found across all investigated ANNs. (edu.au)
For the prediction of joint angles, CNNs appear favourable, however these ANNs do not show an advantage over an MLP network for the prediction of joint moments. (edu.au)
The obtained results showed that ANNs are an ideal tool that can be used to predict Skin Friction Coefficients and Nusselt Number values. (uaeu.ac.ae)
Application of artificial neural networks (ANNs) in drying technology: a comprehensive review. (irost.ir)
The proposed model is a combination of artificial neural networks and stochastic fractal search (SFS−ANNs). (psecommunity.org)
The GOA, WDO, and BBO algorithms are mixed with a class of feedforward artificial neural networks (ANNs), which is called a multi-layer perceptron (MLP) to predict the HL and CL. (psecommunity.org)
Among these, Artificial Neural Networks (ANNs) are complex, nonlinear analysis mathematical systems adapted to recognize patterns with regard to the structures and parameters of the networks chosen for each application. (scirp.org)

The results obtained from the model's performance indices show that a very appropriate prediction has been done for determining the production rate of the chain saw machine by artificial neural networks. (civilejournal.org)
The prediction of future bone mineral density values estimated by artificial neural networks was considered to be useful as a tool to tailor medicine for the early diagnosis of and intervention for women osteoporosis with women. (biomedcentral.com)
If real-time joint angle and joint moment prediction is desirable an LSTM network should be utilised. (edu.au)
Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey. (ac.ir)
Prediction of hydrocarbon densities using an artificial neural network-group contribution method up to high temperatures and pressures. (ac.ir)
Viscosity prediction of ternary mixtures containing ILs using multi-layer perceptron artificial neural network. (ac.ir)
Artificial neural network prediction indicators of density functional theory metal hydride models. (ac.ir)
A targeting signal prediction is, in principle, more reliable than a predicted location based on a close protein ortholog (or on a protein domain), which is itself better than location predicted on the basis of protein composition alone. (biomedcentral.com)
The purpose of this research is to evaluate the applicability of two artificial intelligence techniques including Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) in prediction of precipitation amount before its occurrence. (scialert.net)
In the other hand, as prediction of precipitation plays a crucial role on evaluation and management of drought and flood events, it is very important to be able to predict precipitation before it occurs. (scialert.net)
This work addresses the prediction of dynamic viscosities of several fatty acid esters and biodiesel fuels using a semi-theoretical model and artificial neural network as well. (unich.it)
inproceedings{GCAI2017:Anemic_Status_Prediction_using, author = {Ching Hao Yu and Manas Bhatnagar and Rachel Hogen and Dilin Mao and Atefeh Farzindar and Kiran Dhanireddy}, title = {Anemic Status Prediction using Multilayer Perceptron Neural Network Model}, booktitle = {GCAI 2017. (easychair.org)
Long-Time Prediction of Arrhythmic Cardiac Action Potentials Using Recurrent Neural Networks and Reservoir Computing. (cdc.gov)

Multilayer Perceptron Network (MLP), a class of feedforward Artificial Neural Network (ANN) model was used as the analytical tool. (ijmae.com)

The potential of using three different data-driven techniques namely, multilayer perceptron with backpropagation artificial neural network (MLP), M5 decision tree model, and Takagi-Sugeno (TS) inference system for mimic stage-discharge relationship at Gharraf River system, southern Iraq has been investigated and discussed in this study. (matlabsite.com)
T. Tollenaere, ``SuperSAB: Fast Adaptive Backpropagation with Good Scaling Properties'', Neural Networks 3 , 561 (1990). (lu.se)

These data were incorporated into a multilayer-perceptron (MLP) type artificial neural network (ANN) to model venthole production. (cdc.gov)
The results showed that the two-hidden layer model predicted total production and the methane content of the GGVs with more than 90% accuracy. (cdc.gov)
The ANN model was further used to conduct sensitivity analyses about the mean of the input variables to determine the effect of each input variable on the predicted production performance of GGVs. (cdc.gov)
Some artificial neural networks are adaptive systems and are used for example to model populations and environments, which constantly change. (wikipedia.org)
BP was estimated during activities of daily living using three model architectures: nonlinear autoregressive models with exogenous inputs, feedforward neural network models, and pulse arrival time models. (nature.com)
This work shows that MLP neural networks can accurately model the relationship between local meteorological data and NO 2 and NO x concentrations in an urban environment compared to linear models. (springer.com)
One approach to predict future concentrations is to use a detailed atmospheric diffusion model. (springer.com)
The model was evaluated by the performance indices for artificial neural networks, including the value account for (VAF), root mean square error (RMSE), and coefficient of determination (R 2 ). (civilejournal.org)
Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree. (civilejournal.org)
This paper analyzes the predictability of emerging market currency crises by comparing the often used probit model to a new method, namely a multi-layer perceptron artificial neural network (ANN) model. (europa.eu)
The results reinforced the view that developing a stable model that can predict or even explain currency crises is a challenging task. (europa.eu)
There are 10 neurons in hidden layer of feed forward (FF) back propagation (BP) network model. (uaeu.ac.ae)
When the obtained Mean Square Error (MSE), Coefficient of Determination (R) and error rate values have been analyzed, it has been concluded that the ANN model can predict SFC and NN values with high accuracy. (uaeu.ac.ae)
proposed a multilayer feed forward model [ 16 ]. (hindawi.com)
The specifications of these frames and their analytical results are defined as inputs and targets of artificial neural network and a relatively accurate estimation model of the nonlinear behavior of these beam-columns is presented. (ac.ir)
A total of 1099 data points consisting of alcohol-alcohol, alcohol-alkane, alkane-alkane, alcohol-amine and acid-acid binary solutions were collected from scientific literature to develop an appropriate artificial neural network (ANN) model. (ac.ir)
In this study a multi-layer perceptron artificial neural network model was designed to predict the calcium, sodium, chloride and sulfate ion concentrations of the Karaj River. (irost.ir)
In general, it was found that both ANN and ANFIS models are efficient tool to model and predict precipitation amounts 12 months in advance. (scialert.net)
In this paper, an efficient artificial neural network (ANN) model using multi-layer perceptron (MLP) philosophy has been proposed to predict the fireside corrosion rate of super heater tubes in coal fire boiler assembly, using operational data of an Indian typical thermal power plant. (peacta.org)
We also present a second neural network model that can produce an estimate of the spectral energy distribution of an SN Ia given its phase, color, and twins embedding coordinate. (aas.org)
Sensitivity analysis was performed on over 100 samples of parameter space generated by Latin hypercube sampling method, which was then fed to the ANN model to predict the yield for each sample. (aston.ac.uk)
The PRCC between the predicted yield and each parameter value (input) was used to calculate the sensitivity of the model to each input. (aston.ac.uk)
The goal in the proposed study is to introduce the best statistical model to predict the leakage from dams. (ac.ir)
Then for choosing the best statistical model, some of the most commonly neural network models comprising FFA, RBF, MLP, GEP and SVR were used. (ac.ir)
The performance of both semi-theoretical and ANN model have been checked by predicting dynamic viscosities over the temperature range within 283-393 K and pressures up to 140 MPa with the average absolute relative deviation of 3.10% (for 648 data points) and 0.91% (for 796 data points), respectively. (unich.it)
The ANN model developed herein, has been trained, validated and tested for the set of data gathered, pointing that the efficiency of the neural network model was found excellent on the entire dataset. (unich.it)
This model can be used to predict the risk of clinical events among HD patients and can support decision-making for healthcare professionals. (tmu.edu.tw)
Data of this study are related to the Fajr Industrial Wastewater Treatment Plant located in Mahshahr-Iran that qualitative and quantitative characteristics of its units were used for training, calibration and evaluation of the neural model. (scirp.org)
In the paper, we propose new methods taking into account both unbiased estimates and stem variability: (i) an expert model based on an artificial neural network (ANN) and (ii) a statistical model built using a regression tree (REG). (mdpi.com)
In experiment #2 and experiment #3, the pt-neuron model has predicted threshold values beyond the range of inputs, i.e. (inaya.cloud)
After training the model, we will calculate the accuracy score and print the predicted output on the test data. (inaya.cloud)
Feasibility and Impact of Integrating an Artificial Intelligence-Based Diagnosis Aid for Autism Into the Extension for Community Health Outcomes Autism Primary Care Model: Protocol for a Prospective Observational Study. (cdc.gov)
MRI-Based Back Propagation Neural Network Model as a Powerful Tool for Predicting the Response to Induction Chemotherapy in Locoregionally Advanced Nasopharyngeal Carcinoma. (cdc.gov)

Key ingredients in our approach are a method ($\delta$ -test) for determining relevant inputs and the Multilayer Perceptron. (lu.se)
Using these techniques, parameters that are difficult to directly measure in-the-wild, may be predicted using surrogate lower resolution inputs. (edu.au)

Neural networks can be hardware- (neurons are represented by physical components) or software-based (computer models), and can use a variety of topologies and learning algorithms. (wikipedia.org)
Feedforward networks can be constructed with various types of units, such as binary McCulloch-Pitts neurons, the simplest of which is the perceptron. (wikipedia.org)
Designing of the network architecture is based on the approximation theory of Kolmogorov, and the structure of ANN with 30 neurons had the best performance. (springer.com)
ANN models consist of a multilayer perceptron (MLP) with seven neurons in the input layer, one and two hidden layer(s) with different number of neurons, and an output layer with one neuron. (aston.ac.uk)
Artificial neural network modeling employed a multilayer perceptron comprising one hidden layer and 21 neurons, managed according to the constructive approach. (unich.it)

The feedforward neural network was the first and simplest type. (wikipedia.org)
A probabilistic neural network (PNN) is a four-layer feedforward neural network. (wikipedia.org)

and convolutional neural networks (CNN). (edu.au)

Statistical models by artificial neural networks were superior to those by multiple regression analyses. (biomedcentral.com)

Artificial neural network approach to predict the electrical conductivity and density of Ag-Ni binary alloys. (ac.ir)
Predicting electrical conductivity in Jajrud river by an artificial neural network. (irost.ir)

It was discovered that an artificial neural network with Multilayer Perceptron (MLP) and Random Forest (RF) models could effectively predict the yield, cost, and price of crops. (robotartificial.com)
In this context, we assessed the performance of four ML algorithms (Bagging (BG), Decision Table (DT), Random Forest (RF) and Artificial Neural Network-Multi Layer Perceptron (ANN-MLP)) in predicting maize yield based on four different input scenarios. (unideb.hu)
Three datasets from school level, college level and e-learning platform with varying input parameters are considered for comparison between C5.0, NB, J48, Multilayer Perceptron (MLP), PART, Random Forest, BayesNet, and Artificial Neural Network (ANN). (mecs-press.org)

To that end, we use the renowned Alzheimer's Disease Neuroimaging Initiative (ADNI) data for a handful of neuropsychological tests to train Recurrent Neural Network (RNN) models to predict future neuropsychological test results and Multi-Level Perceptron (MLP) models to diagnose the future cognitive states of trial participants based on those predicted results. (springeropen.com)
Evaluation of Recurrent Neural Network Models for Parkinson's Disease Classification Using Drawing Data. (cdc.gov)

ABSTRACT Models based on an artificial neural network (the multilayer perceptron) and binary logistic regression were compared in their ability to differentiate between disease-free subjects and those with impaired glucose tolerance or diabetes mellitus diagnosed by fasting plasma glucose. (who.int)
The kappa statistics were 0.229 and 0.218 and the area under the ROC curves were 0.760 and 0.770 for the logistic regression and perceptron respectively. (who.int)
There was no performance difference between models based on logistic regression and an artificial neural network for differentiating impaired glucose tolerance/diabetes patients from disease-free patients. (who.int)

A Multi Layer Perceptron, a type of Artificial Neural Network is implemented to predict the poll slope sign. (hu-berlin.de)
In order to predict the (MLP) values, a multi-layer perceptron (MLP) artificial neural network (ANN) has been developed. (uaeu.ac.ae)
In other research project, Jain (2001) predicted suspended sediment load of the Mississippi river and recommended the applicability of multi-layer perceptron ANN for this purpose. (scialert.net)
We present an answer to this question via an extension of the twins embedding technique, using a deep multi-layer perceptron, a simple type of artificial neural network, to accurately predict the phase, extinction parameter, and embedding coordinate of an SN Ia from any single photometrically calibrated spectrum from -10 to +40 rest-frame days after maximum brightness. (aas.org)

In fact, this paper presents the application of these models to predict precipitation in Yazd meteorological station in central Iran with a hyper arid climate condition and very low and highly variable annual rainfall. (scialert.net)
Development and validation of echocardiography-based machine-learning models to predict mortality. (cdc.gov)

CNNs are easier to train than other regular, deep, feed-forward neural networks and have many fewer parameters to estimate. (wikipedia.org)
Here, radiobiological and artificial neural network (ANN) models were used to estimate the normal tissue complication probability (NTCP) of the pituitary gland. (ijrr.com)
We apply Multilayer Perceptron Neural Network to estimate missing values and predict the degree of post-operative anemia. (easychair.org)

Artificial neural networks (ANN) are artificial adaptive systems that simulate certain characteristics of the human brain [ 4 ]. (biomedcentral.com)

Forecasting the differences between various commercial oil prices in the Persian Gulf region by neural network. (irost.ir)
Forecasting nitrate concentration in groundwater using artificial neural network and linear regression models. (irost.ir)

Thus, it is important to understand the effects of various factors, such as drilling parameters, location of borehole, applied vacuum by exhausters and mining/panel parameters in order to be able to evaluate the performance of GGVs and to predict their effectiveness in control ling methane emissions. (cdc.gov)
Image features such as skewness, kurtosis, entropy, mean and standard deviation are given as input parameters for training the neural network and surface roughness value measured experimentally have been given as target values. (inderscience.com)
A regression between input and target parameters has been achieved using neural network to predict the surface roughness of the machined surface. (inderscience.com)
We used hourly NO x and NO 2 concentrations and metrological parameters, automatic monitoring network during October and November 2012 for two monitoring sites (Abrasan and Farmandari sites) in Tabriz, Iran. (springer.com)
Temperature, molecular weight of the pure components, mole fraction of one component and the structural groups of the components were used as input parameters of the network while the refractive index was selected as its output. (ac.ir)
In this study, the multilayer perceptron (MLP) feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. (scirp.org)
Predicting any of these parameters, depending upon the influent water quality, will help the operator to control the system and to take necessary precautions before any problem arisen. (scirp.org)
A better control of a WWTP can be achieved through developing a robust mathematical tool for predicting plant performance based on past observations of certain parameters. (scirp.org)

However, ML implementation to predict maize yield is still limited in Central Europe, especially in Hungary. (unideb.hu)
We further evaluated the performance of the ANN-MLP-SC4 in predicting maize yield on a regional scale (Budapest). (unideb.hu)
This research promotes the use of ANN as an efficient tool for predicting maize yield, which could be highly beneficial for planners and decision makers in developing sustainable plans for crop management. (unideb.hu)
Various artificial neural network (ANN) models were developed to predict grape yield with respect to input energies. (aston.ac.uk)

Artificial neural network application to predict the sawability performance of large diameter circular saws. (civilejournal.org)
Performance Evaluation of Adaptive Neuro-Fuzzy Inference System and Group Method of Data Handling-Type Neural Network for Estimating Wear Rate of Diamond Wire Saw. (civilejournal.org)
According to the results, among different architectures of ANN, dynamic structures including Recurrent Network (RN) and Time Lagged Recurrent Network (TLRN) showed better performance for this application. (scialert.net)
Also, Principal Component Analysis technique was applied to modify and improve performance of generated models of neural networks. (scirp.org)
Hence, conformance testing of such systems is most effectively carried out using Over-The-Air (OTA) testing, since traditional conducted non-spatial test methods will not predict the radiated performance in space and the action of the RF transceiver, in particular the beamformer. (iracon.org)
Predicting academic performance of the student is crucial task as it depends on various factors. (mecs-press.org)
Aucune différence n'a été constatée entre le modèle de régression logistique et celui reposant sur un réseau de neurones artificiels en termes de performance de distinction entre sujets sains et patients présentant une altération de la tolérance au glucose ou un diabète. (who.int)

A time delay neural network (TDNN) is a feedforward architecture for sequential data that recognizes features independent of sequence position. (wikipedia.org)
The second approach is to devise statistical models which attempt to determine the underlying relationship between a set of input data (predictors) and targets (predicted). (springer.com)
The application of artificial intelligence techniques to wearable sensor data may facilitate accurate analysis outside of controlled laboratory settings-the holy grail for gait clinicians and sports scientists looking to bridge the lab to field divide. (edu.au)
artificial neural network (ANN) is the most widely used modeling tool especially in data-constraint regions. (scirp.org)
Multiple Linear Regression (MLR), Multilayer Perceptron Neural Network (MLPNN) and Extreme Learning Machine (ELM) models were used to predict soil temperature from metrological data. (ac.ir)
The most basic definition of data mining is the analysis of large data sets to discover patterns and use those patterns to forecast or predict the likelihood of future events. (ijert.org)
However, in recent decades some data driven techniques such artificial intelligence varieties have shown great ability to deal with non-linear hydrology and water resources problems. (scialert.net)
Establishing a robust and flexible underwater sensing network with reliable data distribution, and sensors capable of estimating the diver pose and hand gestures. (caddy-fp7.eu)
The study used the available stage and discharge data for predicting discharge using different combinations of stage, antecedent stages, and antecedent discharge values. (matlabsite.com)
Only a minority of studies on ovarian cancer have set out to harness artificial intelligence (AI) for the integration of multiomics data and for developing powerful algorithms that capture the characteristics of ovarian cancer at multiple scales and levels. (springeropen.com)
Teaching master courses: Geospatial Artificial Intelligence (GeoAI), Web GIS, Geographical Databases, Spatial Data Infrastructures (SDI). (lu.se)

The results indicated that all models predicted temperature of the top layer (0-30 cm) better than the ones in sublayers. (ac.ir)
Soil temperature estimation using an artificial neural network and co-active neuro-fuzzy inference system in two diﬀerent climates, Arabian Journal of Geosciences , 9(5), 377. (ac.ir)
In these studies some physical and meteorological characteristics of the catchment including drainage area, slope, precipitation, temperature and evaporation were used to predict flow at the outlet of the catchments. (scialert.net)

Machine vision paves a platform to predict the surface roughness of machined surface in non-contact method using CCD camera. (inderscience.com)
In this research, the method of artificial neural networks was used for modeling and predicting the production rate. (civilejournal.org)
Simulation of low TDS and biological units of Fajr industrial wastewater treatment plant using artificial neural network and principal component analysis hybrid method. (irost.ir)
Calibration of the method using predicted values of amino acid exposure allows classifying proteins without 3D-information with an accuracy of 62% and discerning proteins in different locations even if they shared high levels of identity. (biomedcentral.com)
These are the reasons that this study is dedicated to evaluating an innovative hybrid method for predicting the cooling load (CL) in buildings with residential usage. (psecommunity.org)
2005) used Finite Element Method (FEM) and Artificial Neural Network (ANN) models for flow through Jeziorsko Earth fill Dam in Poland. (ac.ir)
We used Artificial Neural Network (ANN) method to predict clinical events during the HD sessions. (tmu.edu.tw)

In this paper, heart patient datasets are investigate for building classification models in order to predict heart diagnosis. (ijert.org)

It has been implemented using a perceptron network whose connection weights were trained with back propagation (supervised learning). (wikipedia.org)
S. E. Fahlman, ``An Empirical Study of Learning Speed in Back-propagation Networks'', Carnegie-Mellon Computer Science Rpt. (lu.se)

have used autoregressive coefficients to predict the weights and biases for time series modeling. (inaya.cloud)

In this study, the results of 367 laboratory specimens collected from the literature are used to present some relations to predict the tensile strength of SFRC using GP. (ac.ir)
The results demonstrate that the predicted cognitive states match the actual cognitive states of ADNI test subjects with a high level of accuracy. (springeropen.com)
The results of the comparison in testing stage reveal that M5 and Takagi-Sugeno techniques have certain advantages for setting up stage-discharge than multilayer perceptron artificial neural network. (matlabsite.com)

High-grade serous ovarian cancer (HGSOC) is the most common type of ovarian cancer and the most lethal gynaecologic malignancy, with 4.32 per 100,000 women predicted to die from ovarian cancer in the European Union in 2022 [ 1 ]. (springeropen.com)
RÉSUMÉ Des modèles reposant sur un réseau de neurones artificiels (de type perceptron multicouche) et sur la régression logistique binaire ont été comparés. (who.int)
0,760 et 0,770 pour la régression logistique et le modèle de type perceptron, respectivement. (who.int)

Trying to answer this question, we use the recent French 2017 presidential election as a case study to predict poll trends based on the emotions in pictures of the candidates in the press. (hu-berlin.de)
Therefore, the present study predicts the production rate of the chain saw machine in dimensional stone quarries. (civilejournal.org)
However, no study has investigated the ability of ANN to predict future BMD and bone loss rate (BLR) values among postmenopausal women. (biomedcentral.com)
Thus, the aim of the present study was to investigate whether ANN models are able to predict future BMD and BLR values from person to person at lumbar and femoral sites of postmenopausal women, respectively, in the future. (biomedcentral.com)
In this study, the complex behavior of steel encased reinforced concrete (SRC) composite beam-columns in biaxial bending is predicted by multilayer perceptron neural network. (ac.ir)
The goal of this study is to identify non-invasive, inexpensive markers and develop neural network models that learn the relationship between those markers and the future cognitive state. (springeropen.com)
The purpose of this study is to predict the areas in financial statements susceptive to fraud in the banking sector of Bangladesh. (ijmae.com)

1397). 'A Comparison Between GA and PSO Algorithms in Training ANN to Predict the Refractive Index of Binary Liquid Solutions', , 52(2), pp. 123-133. (ac.ir)

Two main varieties of artificial intelligence technique which have been widely used to predict natural phenomenon are Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS). (scialert.net)

Value of Artificial Neural Network Ultrasound in Improving Breast Cancer Diagnosis. (cdc.gov)

Despite increased research, there is a paucity of information examining the most suitable artificial neural network (ANN) for predicting gait kinematics and kinetics from IMUs. (edu.au)

Coding a simple neural network from scratch acts as a Proof of Concept in this regard and further strengthens our understanding of neural networks. (inaya.cloud)

於 B. Seroussi, L. Ohno-Machado, L. Ohno-Machado, & B. Seroussi (編輯), MEDINFO 2019: Health and Wellbeing e-Networks for All - Proceedings of the 17th World Congress on Medical and Health Informatics (頁 1570-1571). (tmu.edu.tw)
Tagging B Quark Events in Aleph with Neural Networks'', Proceedings of Workshop in Neural Networks: From Biology to High Energy Physics, June 1991, Elba, Italy , eds. (lu.se)

The main objective of this article is, therefore, to present a powerful combination of techniques originated in Artificial Intelligence - a multidisciplinary field more related to Engineering than to Mathematics, where Statistics has its origins and deductive basis. (bvsalud.org)

Artificial intelligence, specifically machine learning (ML), serves as a valuable tool for decision support in crop management under ongoing climate change. (unideb.hu)
Artificial Neural Network (ANN) has been well recognized as an effective tool in medical science. (easychair.org)

In this network the information moves only from the input layer directly through any hidden layers to the output layer without cycles/loops. (wikipedia.org)
It is a supervised learning network that grows layer by layer, where each layer is trained by regression analysis. (wikipedia.org)
An autoencoder, autoassociator or Diabolo network: 19 is similar to the multilayer perceptron (MLP) - with an input layer, an output layer and one or more hidden layers connecting them. (wikipedia.org)
XOR can be represented by a two-layer neural network. (inaya.cloud)

Statistical extraction of the alpha, beta, theta, delta and gamma brainwaves is performed to generate a large dataset that is then reduced to smaller datasets by feature selection using scores from OneR, Bayes Network, Information Gain, and Symmetrical Uncertainty. (researchgate.net)

Improved assessment of left ventricular ejection fraction using artificial intelligence in echocardiography: A comparative analysis with cardiac magnetic resonance imaging. (cdc.gov)

Artificial neural network approach for predicting transient water levels in a multilayered groundwater system under variable state, pumping, and climate conditions. (irost.ir)

Anatomy1

Analytical, Diagnostic and Therapeutic Techniques and Equipment3

Phenomena and Processes3

Humanities1

Information Science7

Algorithm14

ANNs9

Prediction13

Class of feedforward1

Backpropagation2

Model33

Inputs2

Neurons5

Feedforward neural2

Convolutional neural1

Multiple regression1

Electrical conductivity2

Random Forest3

Recurrent Neural2

Logistic regression3

Multi-layer4

Models to predict2

Estimate3

Adaptive systems1

Forecasting2

Parameters8

Yield4

Performance7

Data11

Temperature3

Method7

Order to predict1

Back propagation2

Coefficients1

Results3

Type3

Study7

Binary1

Inference1

Diagnosis1

Suitable1

Regard1

Proceedings2

Techniques1

Tool2

Layer4

Dataset1

Comparative1

System1