An in-depth experimental study of anomaly detection using gradient boosted machine
This paper proposes an improved detection performance of anomaly-based intrusion detection system (IDS) using gradient boosted machine (GBM). The best parameters of GBM are obtained by performing grid search. The performance of GBM is then compared with ...
Magnetohydrodynamic three-dimensional nonlinear convective flow of viscoelastic nanofluid with heat and mass flux conditions
The present research focuses on three-dimensional nonlinear convective flow of viscoelastic nanofluid. Here, the flow is generated due to stretching of a impermeable surface. The phenomenon of heat transport is analyzed by considering thermal radiation ...
Rule extraction for fatty liver detection using neural networks
Non-alcoholic fatty liver disease (NAFLD) is one of the most common diseases in the world. Recently the FibroScan device is used as a noninvasive, yet costly method to measure the liver's elasticity as a NAFLD indicator. Other than the cost, the ...
Chaotic multi-verse optimizer-based feature selection
The multi-verse optimizer (MVO) is a new evolutionary algorithm inspired by the concepts of multi-verse theory namely, the white/black holes, which represents the interaction between the universes. However, the MVO has some drawbacks, like any other ...
Distributed cooperative learning algorithms using wavelet neural network
This paper investigates the distributed cooperative learning (DCL) problems over networks, where each node only has access to its own data generated by the unknown pattern (map or function) uniformly, and all nodes cooperatively learn the pattern by ...
Correlation measure of hesitant fuzzy soft sets and their application in decision making
Hesitant fuzzy soft set (HFSS) allows each element to have different number of parameters and the values of those parameters are represented by multiple possible membership values. HFSS is considered as a powerful tool to represent uncertain information ...
Assessing the performance of a modified S-transform with probabilistic neural network, support vector machine and nearest neighbour classifiers for single and multiple power quality disturbances identification
This paper presents a substantial assessment between a modified S-transform (MST) and the original S-transform (OST) for the identification of single and multiple power quality disturbances using probabilistic neural network, Gaussian support vector ...
Darcy---Brinkman bio-thermal convection in a suspension of gyrotactic microorganisms in a porous medium
On the basis of Darcy---Brinkman model, linear stability analysis is used to study bio-thermal convection in a suspension of gyrotactic microorganisms in a highly porous medium heated from below. A Galerkin method is performed to solve the governing ...
Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns
Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has ...
The effects of MHD and buoyancy on Hematite water-based fluid past a convectively heated stretching sheet
In the present paper, we examined the buoyancy effects on MHD two-dimensional boundary layer flow in the presence of heat transfer of Hematite---water nanofluid over a stretching sheet. We consider Hematite as nanoparticle and water as its base liquid. ...
Predicting groutability of granular soils using adaptive neuro-fuzzy inference system
In this paper, the applicability of adaptive neuro-fuzzy inference system (ANFIS) for the prediction of groutability of granular soils with cement-based grouts is investigated. A database of 117 grouting case records with relevant geotechnical ...
Performance prediction of roadheaders using ensemble machine learning techniques
Mechanical excavators are widely used in mining, tunneling and civil engineering projects. There are several types of mechanical excavators, such as a roadheader, tunnel boring machine and impact hammer. This is because these tools can bring ...
LU triangularization extreme learning machine in EEG cognitive task classification
Electroencephalography (EEG) has been used as a promising tool for investigation of brain activity during cognitive processes. The aim of this study is to reveal whether EEG signals can be used for classifying cognitive processes: arithmetic tasks and ...
Modified multiple generalized regression neural network models using fuzzy C-means with principal component analysis for noise prediction of offshore platform
A modified multiple generalized regression neural network (GRNN) is proposed to predict the noise level of various compartments onboard of the offshore platform. With limited samples available during the initial design stage, GRNN can cause errors when ...
Handwritten Urdu character recognition using one-dimensional BLSTM classifier
The recognition of cursive script is regarded as a subtle task in optical character recognition due to its varied representation. Every cursive script has different nature and associated challenges. As Urdu is one of cursive language that is derived ...
Intelligent supervision approach based on multilayer neural PCA and nonlinear gain scheduling
This paper is mainly aimed at developing an off-line supervision approach geared to complex processes. This approach consists of two parts: the first part is the fault detection and isolation and the second one is the process control. The first part is ...
Application of artificial neural networks and genetic programming in vapor---liquid equilibrium of C1 to C7 alkane binary mixtures
In this study, the capacity of artificial neural networks (ANNs) and genetic programming (GP) in making possible, fast and reliable predictions of equilibrium compositions of alkane binary mixtures is investigated. A data set comprising 847 data points ...
A discriminative model selection approach and its application to text classification
Classification is one of the fundamental problems in data mining, in which a classification algorithm attempts to construct a classifier from a given set of training instances with class labels. It is well known that some classification algorithms ...
Adaptive pedestrian detection by predicting classifier
Generally the performance of a pedestrian detector will decrease rapidly, when it is trained on a fixed training set but applied to specific scenes. The reason is that in the training set only a few samples are useful for the specific scenes while other ...
Fractional neural observer design for a class of nonlinear fractional chaotic systems
In this paper, a novel observer structure for nonlinear fractional-order systems is presented to estimate the states of fractional-order nonlinear chaotic system with unknown dynamical model. A new fractional error back-propagation learning algorithm is ...
Decision-making tool for crop selection for agriculture development
In the present competitive environment, a farmer needs better education, business expertise and good knowledge of technologies and tools to be successful in agriculture. Farmers usually select crop for cultivation according to their traditional ...
Experimental evaluation of artificial neural network for predicting drainage water and groundwater salinity at various drain depths and spacing
Drainage design parameters of drain depth and spacing are the pivotal factors affect the drain water quality by radial flow of underground water. In this study, artificial neural network modeling has been employed with Levenberg---Marquardt learning ...
Levenberg---Marquardt neural network to estimate UPFC-coordinated PSS parameters to enhance power system stability
Due to the presence of weak tie line interconnections, small signal oscillations are created in power system networks. Damping out these oscillations is one of the most crucial issues to be settled down for the stability of power system industry. The ...
MR-SAS and electric power steering variable universe fuzzy PID integrated control
In order to solve the problem of MR-SAS and electric power steering (EPS) integrated control, the suspension and steering system integrated dynamic model was established, and the variable universe fuzzy PID integrated controller was designed. Due to the ...
