Suitable features selection for the HMLP and MLP networks to identify the shape of aggregate

Isa, Nor Ashidi Mat; Al-Batah, Mohammad Subhi; Zamli, Kamal Z.; Azizli, Khairun Azizi Mohd; Joret, Ariffuddin; Noor, Nor Rizuan Mat

doi:10.1016/j.conbuildmat.2006.08.005

Cited by 22 publications

(5 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In each iteration, one part of the data is held out for testing while the remaining 9 parts are used for training. The results obtained from the ten runs are then averaged (Al-Batah et al, 2009;Isa et al, 2008).…”

Section: Performance Evaluation and Discussionmentioning

confidence: 99%

Arabic Sentiment Classification using MLP Network Hybrid with Naive Bayes Algorithm

Al-Batah¹,

Mrayyen²,

Alzaqebah³

2018

Journal of Computer Science

View full text Add to dashboard Cite

Sentiment analysis has recently become one of the growing areas of research related to text mining and natural language processing. Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites. Most of the current studies related to this topic focus mainly on English texts with very limited resources available for other languages like Arabic. The complexities of Arabic language in morphology, orthography and dialects makes sentiment analysis for Arabic more challenging. In this study, the Naive Bayes algorithm (NB) and Multilayer Perceptron (MLP) network are combined with hybrid system called NB-MLP for Arabic sentiment classification. Five datasets were tested; attraction, hotel, movie, product, and restaurant. The datasets are then classified into positive or negative polarities of sentiment using both standard and combined system. The 10-fold cross validation was employed for splitting the dataset. Over the whole set of experimental data, the results show that the combined system can achieve high classification accuracy and has promising potential application in the Arabic sentiment analysis and opinion mining.

show abstract

Section: Performance Evaluation and Discussionmentioning

confidence: 99%

Arabic Sentiment Classification using MLP Network Hybrid with Naive Bayes Algorithm

Al-Batah¹,

Mrayyen²,

Alzaqebah³

2018

Journal of Computer Science

View full text Add to dashboard Cite

show abstract

“…Meanwhile image segmentation play a key role as using digital image analysis technology, the segmentation results will have a direct impact on image understanding and processing results. To modify the shortage of traditional segmentation methods, A new method based on neural network for image segmentation is used [10][11][12]. The method processes are as followed: Firstly, setting up a neural Applied Mechanics and Materials Vols.…”

Section: Digital Image Processing Methods Of Detecting Wall Shallow C...mentioning

confidence: 99%

Engineering Application of New Wall Materials Anti-Cracking and Anti-Leakage Performance Summary of Several Experiments and Analysis

Jun

Fan

Wang

2013

AMM

View full text Add to dashboard Cite

New wall materials are widely used in the construction industry, which have green environmental protection. But the cracking and leakage wall causes the building function decline, heat preservation and insulation failure, which hinder its comprehensive promotion. Some regularities and conclusions had been got through several researches on the engineering application of new walls anti-cracking and anti-leakage performance. Researches are based on many aspects, such as design calculations, structural measures and detecting techniques. The summary in this paper includes: material crack propagation mechanism, experimental investigation of shrinkage of concrete brick walls at different ages, new walls in-field test of surface permeability, image processing of wall crack etc.

show abstract

“…Also, b j denotes the thresholds in the hidden nodes. Then the predicted output of the kth node in the output layer of the MLP network can be expressed as [28]:…”

Section: Multilayered Perceptron Networkmentioning

confidence: 99%

Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography

Huda

Taib

2013

Infrared Physics & Technology

View full text Add to dashboard Cite

Suitable features selection for the HMLP and MLP networks to identify the shape of aggregate

Cited by 22 publications

References 18 publications

Arabic Sentiment Classification using MLP Network Hybrid with Naive Bayes Algorithm

Arabic Sentiment Classification using MLP Network Hybrid with Naive Bayes Algorithm

Engineering Application of New Wall Materials Anti-Cracking and Anti-Leakage Performance Summary of Several Experiments and Analysis

Suitable features selection for monitoring thermal condition of electrical equipment using infrared thermography

Contact Info

Product

Resources

About