Search Results - model validation ((method algorithm) OR (max algorithm))

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Self-calibration algorithm for a pressure sensor with a real-time approach based on an artificial neural network by M. Almassri, Ahmed M., Wan Hasan, Wan Zuha, Ahmad, Siti Anom, Shafie, Suhaidi, Wada, Chikamune, Horio, Keiichi

“…This paper also shows that the proposed model exhibited a remarkable performance than traditional methods with a max mean square error of 0.17325 and an R-value over 0.99 for the total response of training, testing and validation. …”
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Real time self-calibration algorithm of pressure sensor for robotic hand glove system by Almassri, Ahmed M. M.

“…This work shows that the Proposed model exhibited a remarkable performance than traditional methods with a max MSE of 0.17325 and R value over 0.99 for the total response of training, testing and validation. …”
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Machine learning methods to predict and analyse unconfined compressive strength of stabilised soft soil with polypropylene columns by Hoque, Md. Ikramul, Muzamir, Hasan, Islam, Md Shofiqul, Houda, Moustafa, Abdallah, Mirvat, Sobuz, Md. Habibur Rahman

“…In addition, the sequential model got training loss of 0.2535, training accuracy of 0.9024, validation loss of 0.4056 and validation accuracy: 0.9091. …”
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An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

“…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
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New correlation for oil formation volume factor by Sulaimon, A.A., Ramli, N., Adeyemi, B.J., Saaid, I.M.

“…It is a family of inductive algorithms which executes computer-based mathematical modeling of multi-parametric data sets. …”
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MBIST implementation and evaluation in FPGA based on low-complexity March algorithms by Jidin, Aiman Zakwan, Mispan, Mohd Syafiq, Hussin, Razaidi, Weng, Fook Lee

“…In addition, their fault detection abilities were also validated through tests on a fault-injected memory model, which shows that the implemented March AZ1 and March AZ2 provide 80.6% and 83.3% coverage of the intended faults, respectively, which outperform any other existing 14N-complexity March algorithms.…”
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Quality of service management algorithms in WiMAX networks by Saidu, Ibrahim

“…In addition, an analytical model for the proposed scheme is developed. Secondly, a Load-Aware Weighted Round Robin algorithm (LAWRR) packet scheduling discipline for downlink traffic in 802.16 networks is proposed to improve the poor performance of scheduling algorithm that use static weights under bursty traffic. …”
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Enhanced handover decision algorithm in heterogeneous wireless network by Abdullah, Radhwan Mohammed, Ahmad Zukarnain, Zuriati

“…Finally, the simulation results are validated by the analytical model.…”
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Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

“…Thus, there were three poverty clusters - low, medium, and high - that were used in the model. The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud by Mahmud, Nur Farahana

“…Based on the results obtained, the trained CNN model was able to achieve an accuracy of 97.11% for training and 96.76% for validation, respectively. …”
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Analysis of Toothbrush Rig Parameter Estimation Using Different Model Orders in Real Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The validation test-through correlation analysis was used to validate the model. …”

Analysis of toothbrush rig parameter estimation using different model orders in Real-Coded Genetic Algorithm (RCGA) by Ainul, H. M. Y., Salleh, S. M., Halib, N., Taib, H., Fathi, M. S.

“…The validation test-through correlation analysis was used to validate the model. …”
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Performance of Semi Active Lateral Control (SALC) algorithm for semi active suspension system in multibody co-simulation method / M. M. Abdul Majid ...[et al.] by Abdul Majid, M. M., Salleh, M. S., Abu Hashim, M. A., Ismail, N. H., Mansor, S., Abu Bakar, S. A.

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Optimisation of Environmental Risk Assessment Architecture using Artificial Intelligence Techniques by Salem S. M. Khalifa

“…Two methods were used to validate the proposed architecture, that is, the analytical method was used to validate the neuro-fuzzy risk assessment model and the safe path selection model, whereas the experimental method was used to evaluate the prototype. …”

Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control by Tuan Abdul Rahman, Tuan Ahmad Zahidi, As'arry, Azizan, Abdul Jalil, Nawal Aswan, Raja Ahmad, Raja Mohd Kamil

“…Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. …”
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Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

“…Taguchi?s T-method (T-method) is a predictive modeling technique developed by Dr. …”

Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

“…The model was then fed with new sets of machining parameters to experimentally validate the model’s ability in predicting the cut quality. …”
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An experimental validation and optimisation tool path strategy for thin walled structure by Alsultaney, Hazem K., Mohd Ariffin, Mohd Khairol Anuar, Baharudin, B. T. Hang Tuah, Ali, Aidy, Mustapha, Faizal

“…The target was to develop models which mimic the actual cutting process using the finite element method (FEM), to validate the developed tool path strategy algorithm with the actual machining process and to programme the developed algorithm into the software. …”
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