Search Results - (( using function a algorithm ) OR ( parameter classification modified algorithm ))

Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…The results show that the proposed modified ANFIS architecture with gaussian membership function and Artificial Bee Colony (ABC) optimization algorithm, on average has achieved classification accuracy of 99.5% with 83% less computational complexity.…”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…The analytical model was improved, computing the marking probability can be used in the planning of a network architecture. They can be useful for taking a decision on choosing concrete values of traffic classification environments element parameters in a real network. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…Nevertheless, AC is not required for LCM if the original multi-spectral image is used. The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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RMIL/AG: A new class of nonlinear conjugate gradient for training back propagation algorithm by Basri, S.M.M., Nawi, N.M., Mamat, M., Hamid, N.A.

“…The RMIL uses the value of adaptive gain parameter in the activation function to modify the gradient based search direction. …”
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A framework of modified adaptive neuro-fuzzy inference engine by Hossen, Md. Jakir

“…A modified apriori algorithm was employed to reduce the number of clusters effectively on the basis of common data in the clusters of every input to obtain a minimal set of decision rules based on datasets. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…In this research, a performance analysis based on different activation functions; gradient descent and gradient descent with momentum, for training the BP algorithm with pre-processing techniques was executed. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

“…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

“…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…For this experiment, the modified word vectors serve as input to train a Machine Learning (ML) model for the text classification process, aiming for the developed ML model to have a significantly smaller parameter count. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study by Li Yu Yab, Li Yu Yab, Wahid, Noorhaniza, A Hamid, Rahayu

“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

“…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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Aco-based feature selection algorithm for classification by Al-mazini, Hassan Fouad Abbas

“…The proposed EGCACO algorithm can be utilised for FS in DNA microarray classification tasks that involve large dataset size in various application domains.…”
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Modified symbiotic organisms search optimization for automatic construction of convolutional neural network architectures by Jauro, Fatsuma, Abdullahi, Usman Ali, Abdulsalami, Aminu Onimisi, Ibrahim, Adamu Abubakar, Abdullahi, Mohammed, Chiroma, Haruna

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Analysis of multicomponent transient signals using music superresolution technique by Jibia, Abdussamad Umar, Salami, Momoh Jimoh Emiyoka, Khalifa, Othman Omran

“…A new method of analysis using modified MUSIC (multiple signal classification) subspace algorithm is successfully applied to the analysis of this signal. …”
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Improvement of fuzzy neural network using mine blast algorithm for classification of Malaysian Small Medium Enterprises based on strength by Hussain Talpur, Kashif

“…Mine Blast Algorithm (MBA) which has been improved by Improved MBA (IMBA) can be further improved by modifying its exploitation phase. …”
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Accelerated mine blast algorithm for ANFIS training for solving classification problems by Mohd Salleh, Mohd Najib, Hussain, Kashif

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Three-dimensional craniometrics identification model and cephalic index classification of Malaysian sub-adults: A multi-slice computed tomography study / Sharifah Nabilah Syed Mohd... by Sharifah Nabilah , Syed Mohd Hamdan

“…Discriminant function analysis (DFA), binary logistic regression (BLR), and several machine learning (ML) algorithms (random forest (RF), support vector machines (SVM), and linear discriminant analysis (LDA)) were used to statistically analyse the data. …”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

“…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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An improved back propagation leaning algorithm using second order methods with gain parameter by Mohd Nawi, Nazri, Mohamed Saufi, Noor Haliza, Budiyono, Avon, Abdul Hamid, Noorhamreeza, Rehman Gillani, Syed Muhammad Zubair, Ramli, Azizul Azhar

“…To overcome these limitations, this research proposed a modified approach for BP by introducing the Conjugate Gradient and QuasiNewton which were Second Order methods together with ‘gain’ parameter. …”
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