Search Results - (( moderation classification using algorithm ) OR ( variable activation function algorithm ))

Performance analysis of machine learning algorithms for classification of infection severity levels on rubber leaves by Mat Lazim, Siti Saripa Rabiah, Sulaiman, Zulkefly, Mat Nawi, Nazmi, Mohd Mustafah, Anas

“…The chlorophyll content of each leaf was measured using SPAD meter. Four classification algorithms investigated in this study were artificial neural network (ANN), support vector machine (SVM), knearest neighbour (kNN) and random forest (RF). …”
Get full text
Get full text
Get full text

A Predictive Classification Model For Running Injury by Ganesan, Devesh Raj

“…The J48, SMO, Random Forest, and Simple Logistic algorithms were used for 10-fold cross validation mode classification benchmarked on the ZeroR baseline algorithm. …”
Get full text
Get full text

Classification of basal stem rot disease in oil palm using dielectric spectroscopy by Al-Khaled, Al-Fadhl Yahya Khaled

“…First, features selection algorithms (genetic algorithm (GA), random forest (RF), and support vector machine-feature selection (SVM-FS)) were used to select the most significant frequencies. …”
Get full text
Get full text

Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli by Ramli, Muhammad Harith

“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
Get full text
Get full text

An intra-severity classification and adaptation technique to improve dysarthric speech recognition accuracy / Bassam Ali Qasem Al-Qatab by Bassam Ali Qasem, Al-Qatab

“…Secondly, the identified severity level of a particular dysarthric speaker in the first stage is applied to the corresponding intra-severity adaptation of dysarthric speech. For the classification part, there are six algorithms used to classify the intra-severity of dysarthric speakers. …”
Get full text
Get full text
Get full text

Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations by Hossain, S.K.S., Ayodele, B.V., Alhulaybi, Z.A., Alwi, M.M.A.

“…The RBFNN model with softmax as the hidden layer activation function and identity as the outer layer activation function has the least predictive performance, as indicated by an R2 of 0.403 and a RMSE of 301.55. …”
Get full text
Get full text

Mid-infrared spectroscopy for early detection of basal stem rot disease in oil palm by Liaghat, Shohreh, Mansor, Shattri, Ehsani, Reza, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja

“…The selected principal component scores were used in classification using linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbor (kNN) and Naive-Bayes (NB) multivariate classification algorithms. …”
Get full text
Get full text

Shunt active power filter using hybrid fuzzy-proportional and crisp-integral control algorithms for total harmonic distortion improvement by Abdul Rahman, Nor Farahaida

“…Utilization of soft-computing algorithms in the operation of Shunt Active Power Filters (SAPFs) becomes a latest trend. …”
Get full text
Get full text

Classification of Distracted Male Driver Based on Driving Performance Indicator (DPI) by Ganasan, Shatiskumar, Norazlianie, Sazali

“…We applied these algorithms on their datasets using its GUI or command-line parameters. …”
Get full text
Get full text
Get full text
Get full text

Real time De-mixing system based on LMS adaptive algorithm for blind two source signals separation by Mehrkanoon, S., Moghavvemi, M., Fariborzi, H.

“…The time variant mixing matrix based on random vector with time variable elements are made. Several simulations obtain optimum results of implemented algorithm. …”
Get full text

Backpropagation vs. radial basis function neural model : Rainfall intensity classification for flood prediction using meteorology data by Chai, S.S., Wong, W.K., Goh, K.L.

“…Among the various soft computing methods, Artificial Neural Network (ANN) is the most commonly used methodology. While numerous ANN algorithms were applied, the most commonly applied are the Backpropagation (BPN) and Radial Basis Function (RFN) models. …”
Get full text
Get full text
Get full text

Classification of Mental Health Level of Students Using SMOTE and Soft Voting Ensemble Classifier and the DASS-21 Profile by Muhammad Imron, Rosadi, Khoirun, Nisa, Nanik, Kholifah

“…It leverages the Synthetic Minority Over-sampling Technique (SMOTE) to address the class imbalance in the dataset and employs a Voting Ensemble with soft voting to combine several base algorithms (Logistic Regression, Random Forest, Gradient Boosting, and XGBoost/SVM) for accurate prediction of mental health levels (normal, mild, moderate, severe, very severe). …”
Get full text
Get full text
Get full text
Get full text

Moving vehicle noise classification using backpropagation algorithm by Norasmadi, Abdul Rahim, Paulraj, Murugesa Pandiyan, Assoc. Prof., Abdul Hamid, Adom, Assoc. Prof. Dr., Sundararaj, Sathishkumar

Get full text

Automatic diabetic retinopathy detection and classification system by Omar, Zainab Awatif, Hanafi, Marsyita, Mashohor, Syamsiah, Mahfudz, Nur Faten Munirah, Abdul Muna'aim, Maimunah

Get full text
Get full text

Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
Get full text
Get full text
Get full text

Early detection of basal stem rot disease (Ganoderma) in oil palms based on hyperspectral reflectance data using pattern recognition algorithms by Liaghat, Shohreh, Ehsani, Reza, Mansor, Shattri, Mohd Shafri, Helmi Zulhaidi, Meon, Sariah, Sankaran, Sindhuja, Azam, Siti H. M. N.

Get full text
Get full text

MotionSure: a cloud-based algorithm for detection of injected object in data in motion by Islam, Thouhedul, Olanrewaju, Rashidah Funke, Khalifa, Othman Omran

“…Mostly, the Man In The Middle (MITM) attack happens in this stage by hijacking active session variables, manipulating files and objects. …”
Get full text
Get full text
Get full text
Get full text

A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., M. S. A., Radzak, Musa, Mailah, Nukman, Yusoff, Abd Razak, Bushroa, Mohd Sayuti, Ab. Karim, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Abdullah Nasser, Mohammed Abdullah, Abdulghafor, Rawad

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
Get full text
Get full text
Get full text
Get full text

A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A. H., Radzak, Muhammad S. A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab.Karim, Mohd Sayuti, Ameen, Wadea, Jabbar, Waheb A., Alsewari, Abdulrahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulghafor, Rawad

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
Get full text
Get full text
Get full text
Get full text

A novel inertia moment estimation algorithm collaborated with active force control scheme for wheeled mobile robot control in constrained environments by Ali, Mohammed A.H., Radzak, Muhammad S.A., Mailah, Musa, Yusoff, Nukman, Abd Razak, Bushroa, Ab. Karim, Mohd Sayuti, Ameen, Wadea, A. Jabbar, Waheb, Alsewari, AbdulRahman A., Rassem, Taha H., Nasser, Abdullah B., Abdulmolla Abdulghafor, Rawad Abdulkhaleq

“…The estimation is accomplished by calculating the membership function based on the experts’ views in any form (symmetric or non-symmetric) with lowly or highly overlapped linguistic variables. …”
Get full text
Get full text
Get full text
Get full text
Get full text