[PDF] Top 20 Improved cuckoo search based neural network learning algorithms for data classification
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Improved cuckoo search based neural network learning algorithms for data classification
... Seeing the problem of convergence in deterministic methods, many nature inspired meta-heuristic methods have been used to solve non-linear optimization problems, such as; artificial bee colony (ABC) algorithm (Karaboga, ... See full document
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A functional link neural network with modified cuckoo search for prediction tasks
... (MLP) network model is already well-established based on problem solving in pattern recognition (Ghazali & Al-Jumeily, 2009), classification (Fallahnezhad et ...of network that lie in HONN ... See full document
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
... Recurrent neural network (RNN) has been widely used as a tool in the data ...This network can be educated with gradient descent back ...training algorithms have some drawbacks such as ... See full document
13
A HYBRID MODEL FOR CLASSIFYING PLANT STRESSES
... EEP learning (DL) is considered one of the dynamic research areas comprehensively and effectively applied in different ...is based on algorithms for learning multiple levels of representation ... See full document
5
Classification of Cardiotocogram Data using Neural Network based Machine Learning Technique
... ANN based classifier provided excellent average performance, if we carefully watch the results of ten trials with ANN (the last table in annexure), we may find another weakness of this ...machine learning ... See full document
7
A new back propagation neural network optimized with cuckoo search algorithm
... Back-propagation Neural Network (BPNN) algorithm is one of the most widely used and a popular technique to optimize the feed forward neural network ...meta-heuristic algorithms provide ... See full document
14
Cuckoo Search based Hybrid Classification Techniques
... high classification accuracy of SVMs are taken by the proposed SVM based Binary Decision Tree ...multi-class classification performance, requires much less computation for deciding a class for an ... See full document
5
Research on image classification model based on deep convolution neural network
... CNN based ap- ...several data sets, we discuss a new direction of general and special case re- ...Convolution neural network (CNN) is very inter- ested in machine learning and has ... See full document
11
Streamlining Object Oriented Programming Approach based on Cuckoo Search Back Propagation Neural Network
... various algorithms is used in the OOP technique like GA, ACO and ICA, which solves the optimization ...input data. The FCA arranges the data in the lattice manner, which helps the proposed method to ... See full document
8
Improved sequential and batch learning in neural networks using the tangent plane algorithm
... machine learning repository ...the data is inexact or contains a small number of erroneous ...the network to satisfy each new constraint in ...gave improved convergence, smaller steps taken ... See full document
232
Big Data Classification Based On Forest Deep Neural Network
... machine learning technique where initially the big data is split into 𝑚 parts and then a set of training sets is generated by randomly sample with replacement of size 𝑁 (bootstrap) from the original ... See full document
5
A Data Classification Algorithm of Internet of Things Based on Neural Network
... times, network accuracy has shown a rapid drop ...the network undergoes a weight correction flat area between 200 and 2500 ...the network should speed up the learning step, so as to achieve ... See full document
10
Kidney Images Classification Using Cuckoo Search Algorithm And Artificial Neural Network
... vast data and good quality of information to detect the ...had improved the accuracy of the system or proved to be best in accuracy for classifying the kidney ...the classification accuracy will be ... See full document
6
The use of adversaries for optimal neural network training
... size, learning rate, training steps ...TensorFlow network was found using HyperBand [9], which narrows down the best configuration from a large random sample of hyper-parameter ...testing data-set ... See full document
8
Comparative Study of Optimized Wireless Sensor Network Routing Protocols
... In the last period , due to widely use of wireless sensor networks in different applications as military surveillance[1], environment monitoring[2], infrastructure protection[3] etc. WSN is considered as one of the most ... See full document
8
Exploring Ant Lion Optimization Algorithm to Enhance the Choice of an Appropriate Software Reliability Growth Model
... In this work, we develop the technique proposed in[5] for solving the problem of choice the best software reliability growth model Which fits to certain dataset, we used an ant lion algorithm to estimating the parameters ... See full document
8
Neural Network Based Rainfall Prediction
... forward neural network popularly called as multilayer perceptrons consists of multiple layers of computational units, usually interconnected in a feed-forward ...rainfall data by using previous rain ... See full document
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A Comparative Study of Machine Learning Algorithms and Their Ensembles for Botnet Detection
... DOI: 10.4236/jcc.2018.65010 127 Journal of Computer and Communications While the ensemble methods offered by Scikit-learn are not significantly beneficial on each algorithm, random forest appears highly effective in ... See full document
11
Opinion Mining of M Learning Reviews using Soft Computing Techniques
... for classification uses group of classification trees [11], which is not as rational as decision ...of learning used in random forest is that the integration of multiple unstable classifiers will ... See full document
5
Beat classification of an ecg signal using photoplethysmography and neural network
... tele-monitoring technology. PPG-based estimation of respiration rate is desirable, given that heart rate and oxygen saturation can also be derived from the same probe, but the analysis of respiratory-induced ... See full document
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