Search Results - (( training effectiveness data algorithm ) OR ( java implication based algorithm ))

Effect of normalization and effect of normalization and training algorithm on radial basis training algorithm on radial basis function network performance function network performa... by Wani, Eddie

“…To recognize the effect of normalization of data and training algorithm on Radial Basis Function (RBF) performance.…”
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Sentiment classification for malay newspaper using clonal selection algorithm / Nur Fitri Nabila Mohamad Nasir by Mohamad Nasir, Nur Fitri Nabila

“…The experimental results show that our method can achieve better performance in clonal selection algorithm sentiment classification and the data collected cannot be used at once in this model because training data is very time-consuming if using all the data. …”
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XCOA-MLP: Extended Coyote Optimization Algorithm for training neural networks in medical data classification by Al-Asaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

“…These findings demonstrate XCOA-MLP’s effectiveness in improving neural network training for medical data classification.…”
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Dynamic training rate for backpropagation learning algorithm by Al-Duais, M. S., Yaakub, Abdul Razak, Yusoff, Nooraini

“…In this paper, we created a dynamic function training rate for the Back propagation learning algorithm to avoid the local minimum and to speed up training.The Back propagation with dynamic training rate (BPDR) algorithm uses the sigmoid function.The 2-dimensional XOR problem and iris data were used as benchmarks to test the effects of the dynamic training rate formulated in this paper.The results of these experiments demonstrate that the BPDR algorithm is advantageous with regards to both generalization performance and training speed. …”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

“…From the experimental results, the dynamic algorithm provides superior performance in terms of faster training with highest accuracy training compared to the manual algorithm. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm by Abubakar, Adamu, Chiroma, Haruna, Khan, Abdullah, Mohamed, Elbaraa Eldaw Elnour

“…This study utilized raw data from network traffic and built a Neural Network (NN) model trained with the Cuckoo Search (CS) algorithm. …”
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Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[... by Idris, N. H., Salim, N. A., Othman, M. M., Yasin, Z. M.

“…Artificial Neural Network (ANN) is one of the problem solver with variety of training algorithms that helps to predict the cascading collapse occurrence due to the hidden failure effect. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

“…The theoretical foundation of this algorithm will be studied and summarized. Simulation experiment results on training and testing data will be recorded and discussed.…”
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A novel strategy for speed up training for back propagation algorithm via dynamic adaptive the weight training in artificial neural network by Al-Duais, Mohameed Sarhan, Yaakub, Abd Razak, Yusoff, Nooraini, Ahmad, Faudziah

“…The drawback of the Back Propagation (BP) algorithm is slow training and easily convergence to the local minimum and suffers from saturation training.To overcome those problems, we created a new dynamic function for each training rate and momentum term.In this study, we presented the (BPDRM) algorithm, which training with dynamic training rate and momentum term. …”
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Development of classification algorithms of human gait by Koh, Chee Hong

“…Thus, this study aims to develop a classification algorithm that can effectively classify subjects with relatively simplified input data. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process by Ali Al-Assadi, Hayder M. A.

“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. Supervised classification of remotely sensed data requires systematic collection of training samples for classes of interest. …”
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Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

“…Water level data set was chosen to test the proposed IABO-trained algorithm. …”
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Autoreclosure in Extra High Voltage Lines using Taguchi’s Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Ramarao, Taj, Mohammed Baloch

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Autoreclosure in Extra High Voltage Lines using Taguchi's Method and Optimized Neural Networks by Desta, Zahlay F., K.S., Rama Rao

“…The developed algorithm is effectively trained, verified and validated with a set of training, dedicated testing and validation data respectively.…”
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Analysis of air quality index (AQI) in Klang valley using artificial neural network (ANN) technique / Rosli Idris by Idris, Rosli

“…Between these three methods, the Levenberg-Marquardt Algorithms is the best method for analyzing AQI data with the lowest error of data during training process which is from -0.5569 to 0.5787 and also has the fastest learning or training the AQI data.…”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids by Chiaverini, Luca, Macdonald, David W., Hearn, Andrew J., Kaszta, Zaneta, Ash, Eric, Bothwell, Helen M., Can, Ozgun Emre, Channa, Phan, Clements, Gopalasamy Reuben *, Haidir, Iding Achmad, Kyaw, Pyae Phyoe, Moore, Jonathan H., Rasphone, Akchousanh, Tan, Cedric Kai Wei, Cushman, Samuel A.

“…Other approaches have been developed to produce robust SDMs, like training data bootstrapping and spatial scale optimisation. …”
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Enhanced mechanism to handle missing data of Hadith classifier by Aldhlan, Kawther A., Zeki, Ahmed M., Zeki, Akram M.

“…Decision tree algorithms have the ability to deal with missing values or wrong data. …”
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Application of adaptive network based fuzzy inference system for model reconstruction in reverse engineering by Nagajyothi, D.

“…The trained ANFIS is taken as surface data model. By comparing the surface data, which is from trained ANFIS, with the data sample value, it can be found that the ANFIS model can match the real surface very well.…”
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