26 results for “Hidden Layer”

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Research ArticleOpen accessPhrase in the titleEffect of Hidden Layer Neurons on the Classification of Optical Character Recognition Typed Arabic NumeralsNidal F. Shilbayeh, Mahmoud Z. IskandaraniProblem statement: The effect of varying the number of nodes in the hidden layer and number of iterations are important factors in the recognition rate. In this paper, a novel and effective criterion based on Cross Pruning (CP) algorithm is proposed to optimize number of hidden neurons and number of iterations in Multi Layer Perceptron (MLP) neural based recognition system. … …Journal of Computer Science, Vol. 4, Issue 7 · 31 Jul 2008 · 7,556 accessesView PDF Cite

Research ArticleOpen accessEvery word in the titleA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEvaluation of Surface Drag Interval in the Variable SituationsParisa Ashrafi, Amir Hossein Ashrafi, Hossein Gholami et al.Tools applied in different fields of engineering are artificial neural networks to model non-linear systems which are efficient and useful. Artificial neural networks consist of input and output layers with one or more hidden layers between them. In fact, one or more processing elements or neurons are used in each layer. Input layer neurons are the independent variables studied and … …American Journal of Engineering and Applied Sciences, Vol. 15, Issue 1 · 12 Mar 2022 · 6,001 accessesView PDF Cite

Research ArticleOpen accessIn the abstractThe Optimized Extreme Learning Machine (GA-OELM) for DDoS Attack Detection in Cloud EnvironmentMeryem Ec-Sabery, Adil Ben Abbou, Abdelali Boushaba et al.The widespread adoption of cloud computing has increased the attack surface and raised significant security concerns. A Distributed Denial of Service (DDoS) is a serious attack that depletes the network and server resources in cloud computing, causing service downtime or reduced performance. Therefore, defending against DDoS attacks becomes an urgent need. In this present paper, we propose an Optimized Extreme … …Journal of Computer Science, Vol. 21, Issue 1 · 19 Dec 2024 · 5,033 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPredicting Depression Levels using Back Propagation Neural NetworkEddy Muntina Dharma, Yaya Heryadi, Lukas et al.Depression is a mood disorder characterized by feelings of deep sadness and a sense of indifference. When depression recurs in moderate or severe intensity, it can be a serious health condition. The most effective way to deal with this problem is to predict the symptoms of depression at an early stage. In this study, a Back Propagation Neural Network (BPNN) … …Journal of Computer Science, Vol. 18, Issue 3 · 18 Mar 2022 · 6,882 accessesView PDF Cite

Research ArticleOpen accessIn the abstractOptimization of Multi-Layer Perceptron Deep Neural Networks using Genetic Algorithms for Hand Gesture RecognitionKhanh Nguyen-Trong, Thi-Thanh-Tan NguyenApplications of wearable sensors for Hand Gesture Recognition (HGR) have been gaining popularity in recent years. Among the proposed methods, deep neural networks with many hidden layers are promising to address the requirements of this wearable activity recognition. They can directly uncover features tied to the dynamics of HGR, from simple motion encoding in lower layers to more complex motion … …Journal of Computer Science, Vol. 18, Issue 2 · 8 Feb 2022 · 7,180 accessesView PDF Cite

Review ArticleOpen accessIn the abstractDeep Learning Approach for Human Action Recognition Using Gated Recurrent Unit Neural Networks and Motion AnalysisNeziha Jaouedi, Noureddine Boujnah, Med Salim BouhlelHuman action recognition is a computer vision task. The evaluation of action recognition algorithms relies on the proper extraction and learning of the data. The success of the deep learning and especially learning layer by layer led to many imposing results in several contexts that include neural network. Here the Recurrent Neural Networks (RNN) with hidden unit has demonstrated advanced … …Journal of Computer Science, Vol. 15, Issue 7 · 29 Jul 2019 · 8,018 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEstimation of Soils Electrical Resistivity using Artificial Neural Network ApproachKpomonè Komla Apaloo-Bara, Adekunlé Akim Salami, Mawugno Koffi Kodjo et al.The knowledge of the ground electrical resistivity is essential to ensure the protection of electrical and telecommunications networks. However, the monitoring of its values is an expensive task which takes long time. Therefore, its prediction is important. This study investigates on predicting soil electrical resistivity using Artificial Neural Networks. Nine sites of our city (Lome, TOGO) were considered. After characterization … …American Journal of Applied Sciences, Vol. 16, Issue 2 · 13 Mar 2019 · 9,518 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCharacterization of the Changes in Opened Sufu Bottles During Storage with Mathematical ModelJingJing Liang, Dawei Li, Ruiqin Shi et al.Artificial Neural Network (ANN) is a type of nonlinear empirical model, which can clarify the complex relation between the inputs and outputs that allows it to approximate any nonlinear function for making predictions. The objective of this study is to monitor the Biogenic Amines (BAs) content and selected physicochemical properties of sufu (a traditional Chinese fermented soybean product) along time. … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 12 Dec 2018 · 9,353 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Deep Convolutional Neural Wavelet Network for Classification of Medical ImagesRamzi Ben Ali, Ridha Ejbali, Mourad ZaiedThis work present a new solution for medical image classification using the Neural Network (NN) and Wavelet Network (WN) based on the Fast Wavelet Transform (FWT) and the Adaboost algorithm. This method is divided in two stages: The learning stage and the classification stage. The first consists to extract the features using the FWT based on the MultiResolution Analysis (MRA). … …Journal of Computer Science, Vol. 14, Issue 11 · 11 Nov 2018 · 7,620 accessesView PDF Cite