Search Results - ((marking algorithm) OR (((((means algorithm) OR (learning algorithm))) OR (based algorithm))))

Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm by Sophian, Ali, Azmi, Nur Hanisah, Bawono, Ali Aryo

“…In this work, preliminary study of the implementation of one of the latest deep learning algorithms, i.e. YOLOv5, has been carried out in the detection and classification of missing road lane markings. …”
Get full text
Get full text
Get full text
Get full text

Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

Subjects:

A WEB-BASED SYSTEM FOR THE PREDICTION OF STUDENT PERFORMANCE IN UPCOMING PUBLIC EXAMS BASED ON ACADEMIC RECORDS by DELLON, NELSON BRUNNIE

“…Teachers will be able to precisely forecast their students' impending grades utilizing the system's web-based application integration and machine learning algorithms. …”
Get full text
Get full text

Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population by Yahaya, Yasmin Arijah Che

“…This study analysed the Phenice method by utilising 3D CT scans by deep learning algorithm for sex estimation and age estimation. …”
Get full text
Get full text

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
Get full text
Get full text

A soft hierarchical algorithm for the clustering of multiple bioactive chemical compounds by Salim, Naomie, Shah, J. Z.

“…The results of the algorithm show significant improvement in comparison to a similar implementation of the hard c-means algorithm.…”
Get full text
Get full text
Get full text

Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

“…The studies had found that k-Medoids produced higher accuracy result with 0.11% higher than k-Means. As a conclusion, with this type of data, k-Medoids algorithm had shown higher accuracy result rather than k-Means.…”
Get full text
Get full text

Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
Get full text
Get full text

Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model by Sulaiman, Md. Nasir, Mohamed, Raihani, Mustapha, Norwati, Zainudin, Muhammad Noorazlan Shah

“…In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
Get full text
Get full text
Get full text

Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin by Hussin, Noor Rasyidah

“…During the training process, bat algorithm is search the best one for number of neurons in hidden layer, learning rate and momentum rate which at the same time result the lowest mean absolute percentage error. …”
Get full text
Get full text

Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques by Lipu M.S.H., Hussain A., Saad M.H.M., Hannan M.A.

“…Backpropagation algorithms; Errors; Learning algorithms; Mean square error; Neural networks; Particle swarm optimization (PSO); Torsional stress; Back propagation neural networks; Backtracking search algorithms; Heuristic optimization technique; Optimal neural network; Optimization algorithms; Particle swarm optimization algorithm; Root mean square errors; state of energy; Lithium-ion batteries…”

Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection by Sevamalai, Venantius Kumar

“…Therefore a study was conducted to introduce a new algorithm to inspect integrated circuit package markings. …”
Get full text
Get full text

Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

“…For fingerprint database optimisation, novel access point (AP) selection algorithms which are based on variant AP selection are investigated to improve computational accuracy compared to existing AP selection algorithms such as Max-Mean and InfoGain. …”
Get full text
Get full text

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

Subjects:

A modified generalized RBF model with EM-based learning algorithm for medical applications by Ma, Li Ya, Abdul Rahman, Abdul Wahab, Quek, Chai

“…Moreover, GRBF trained by the new algorithm has an apparent statistical meaning. Experimental results show potentials for real-life applications.…”
Get full text
Get full text
Get full text

Experimental implementation controlled SPWM inverter based harmony search algorithm by Najeeb M., Mansor M., Razali R., Daniyal H., Yahaya J.A.F.

“…C (programming language); Controllers; Electric inverters; Errors; Learning algorithms; MATLAB; Particle swarm optimization (PSO); Pulse width modulation; Voltage control; And transient response; C code for the sine PWM; C++ codes; Ezdsp f28335 board; Harmony search algorithm; Harmony search algorithms; Mean absolute error; Pulse width modulation inverters; Sinusoidal pulsewidth modulations (SPWM); Transient analysis…”

Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
Get full text
Get full text

An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…Linear discriminant analysis (LDA) is a very popular method for dimensionality reduction in machine learning. Yet, the LDA cannot be implemented directly on unsupervised data as it requires the presence of class labels to train the algorithm. …”
Get full text
Get full text
Get full text

Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

“…This study constructs the flow of DNN based method with the K-Means algorithm. DNN techniques is suitable in solving nonlinear and complex problem. …”
Get full text
Get full text
Get full text

A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

“…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
Get full text
Get full text