A deep learning based artificial neural network approach for intrusion detection
SS Roy, A Mallik, R Gulati, MS Obaidat… - … and Computing: Third …, 2017 - Springer
Security of data is considered to be one of the most important concerns in today's world.
Data is vulnerable to various types of intrusion attacks that may reduce the utility of any …
Data is vulnerable to various types of intrusion attacks that may reduce the utility of any …
Design of building construction safety prediction model based on optimized BP neural network algorithm
In order to solve the safety problem of the construction industry, the construction safety
prediction model based on the optimized BP neural network algorithm is designed in this …
prediction model based on the optimized BP neural network algorithm is designed in this …
Natural language generation using sequential models: a survey
Abstract Natural Language Generation (NLG) is one of the most critical yet challenging tasks
in all Natural Language Processing applications. It is a process to automate text generation …
in all Natural Language Processing applications. It is a process to automate text generation …
Email-Based cyberstalking detection on textual data using Multi-Model soft voting technique of machine learning approach
In the virtual world, many internet applications are used by a mass of people for several
purposes. Internet applications are the basic needs of people in the modern days of lifestyle …
purposes. Internet applications are the basic needs of people in the modern days of lifestyle …
Spam email detection using deep support vector machine, support vector machine and artificial neural network
Emails are a very important part of our life today for information sharing. It is used for both
personal communication as well as business purposes. But the internet also opens up the …
personal communication as well as business purposes. But the internet also opens up the …
Classifying multi-category images using deep learning: a convolutional neural network model
A Bandhu, SS Roy - … Recent Trends in Electronics, Information & …, 2017 - ieeexplore.ieee.org
This paper presents an image classification model using a convolutional neural network with
Tensor Flow. Tensor Flow is a popular open source library for machine learning and deep …
Tensor Flow. Tensor Flow is a popular open source library for machine learning and deep …
Protein sequence classification using convolutional neural network and natural language processing
Classifying protein sequences from biological data has lot of importance in the field of
pharmacology. The application of machine learning to find the sequence of amino acids has …
pharmacology. The application of machine learning to find the sequence of amino acids has …
Predicting ozone layer concentration using multivariate adaptive regression splines, random forest and classification and regression tree
Air pollution is one of the major environmental worries in recent time. Abrupt increase in the
concentration of any gas leads to air pollution. The cities are mostly affected due to the …
concentration of any gas leads to air pollution. The cities are mostly affected due to the …
Prediction of customer satisfaction using Naive Bayes, multiclass classifier, K-star and IBK
Customer satisfaction is an important term in business as well as marketing as it surely
indicates how well the customer expectations have been met with by the product or the …
indicates how well the customer expectations have been met with by the product or the …
Predicting longitudinal dispersion coefficient in natural streams using minimax probability machine regression and multivariate adaptive regression spline
This article employs minimax probability machine regression (MPMR) and multivariate
adaptive regression spline (MARS) for prediction of longitudinal dispersion coefficient in …
adaptive regression spline (MARS) for prediction of longitudinal dispersion coefficient in …