scholarly journals Sentiment Analysis of Movie Opinion in Twitter Using Dynamic Convolutional Neural Network Algorithm

2018 ◽  
Vol 12 (1) ◽  
pp. 1 ◽  
Author(s):  
Fajar Ratnawati ◽  
Edi Winarko
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Sentiment Analysis ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Test Results ◽  
Network Algorithm ◽  
The People ◽  
Neural Network Algorithm ◽  
F Measure

Movie has unique characteristics. When someone writes an opinions about a movie, not only the story in the movie itself is written, but also the people involved in the movie are also written. Opinion ordinary movie written in social media primarily  twitter.To get a tendency of opinion on the movie, whether opinion is likely  positive, negative or neutral, it takes a sentiment analysis. This study aims to classify the sentiment is positive, negative and neutral from opinions Indonesian language movie and look for the accuracy, precission, recall and f-meausre of the method used is Dynamic Convolutional Neural Network. The test results on a system that is built to show that Dynamic Convolutional Neural Network algorithm provides accuracy results better than Naive Bayes method, the value of accuracy of 80,99%, the value of precission 81,00%, recall 81,00%, f-measure 79,00%   while the value of the resulting accuracy Naive Bayes amounted to 76,21%, precission 78,00%, recall 76,00%, f-measure 75,00%.

scholarly journals EQUIPMENT PRICE FORECAST BASED ON T-S FUZZY NEURAL NETWORK

2018 ◽  
Vol 48 (4) ◽  
pp. 305-309
Author(s):  
G. P. JIANG ◽  
L. XIE ◽  
S. X. SUN
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Test Results ◽  
Factors Affecting ◽  
Price Forecast ◽  
Network Algorithm ◽  
Auction Price ◽  
Variable Weight ◽  
Fuzzy Neural ◽  
Neural Network Algorithm

As we all know, the factors affecting the price of equipment are more complicated, but these factors still have a great correlation. How can we accurately predict the price of equipment? Based on the study of the tight support and smoothness of wavelet function, this paper proposes a correlation variable weight wavelet neural network algorithm to predict the price of 162 devices. The test results show that if the weight is not reduced, the predicted price is 0, and the error is still large. However, by arranging the data from small to large, the variable weighted wavelet neural network algorithm is used to predict the result closer to the auction price, which overcomes the incompatibility of the algorithm iteration and provides a reference for accurately predicting the price of the device.

Classification of Batik Authenticity Using Convolutional Neural Network Algorithm with Transfer Learning Method

2021 ◽  
Author(s):  
Farrel Athaillah Putra ◽  
Dwi Anggun Cahyati Jamil ◽  
Briliantino Abhista Prabandanu ◽  
Suhaili Faruq ◽  
Firsta Adi Pradana ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
Learning Method ◽  
Network Algorithm ◽  
Neural Network Algorithm

scholarly journals proABC-2: PRediction Of AntiBody Contacts v2 and its application to information-driven docking

2020 ◽  
Author(s):  
F. Ambrosetti ◽  
T. H. Olsen ◽  
P. P. Olimpieri ◽  
B. Jiménez-García ◽  
E. Milanetti ◽  
...  
Keyword(s):  
Neural Network ◽  
Monoclonal Antibodies ◽  
Random Forest ◽  
Convolutional Neural Network ◽  
Rational Design ◽  
Computational Approaches ◽  
Fundamental Step ◽  
Link Type ◽  
Network Algorithm ◽  
Neural Network Algorithm

AbstractMonoclonal antibodies (mAbs) are essential tools in the contemporary therapeutic armoury. Understanding how these recognize their antigen is a fundamental step in their rational design and engineering. The rising amount of publicly available data is catalysing the development of computational approaches able to offer valuable, faster and cheaper alternatives to classical experimental methodologies used for the study of antibody-antigen complexes.Here we present proABC-2, an update of the original random-forest antibody paratope predictor, based on a convolutional neural network algorithm. We also demonstrate how the predictions can be fruitfully used to drive the docking in HADDOCK.The proABC-2 server is freely available at: https://bianca.science.uu.nl/proabc2/.

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