Search Results - (( program learning means algorithm ) OR ( java application reoptimize algorithm ))

Computational Thinking Through Unplugged Programming Activities : Exploring Students’ Learning Experiences by Lim, Bih Loong

“…The result shows that there is no significant effect of the learning material in increasing the participants’ algorithm skill. …”
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The impact of virtual reality on programming algorithm courses on student learning outcomes by Dewi, Ika Parma, Ambiyar, Effendi, Hansi, Giatman, Muhammad, Hanafi, Hafizul Fahri, Ali, Siti Khadijah

“…Therefore, learning with VR effectively improves student learning outcomes on programming algorithm materials. …”
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Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

“…In the financial sector, machine learning algorithms are used to detect fraud, automate trading, and provide financial advice to investors. …”
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Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

“…Different teaching approaches for programming are widespread but what is essential for students is being able to computationally formulate an algorithmic solution at first and then transfer to code. …”
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement by Balasubramaniyan, Divager, Husin, Nor Azura, Mustapha, Norwati, Mohd Sharef, Nurfadhlina, Mohd Aris, Teh Noranis

“…The entire research implementation result is carried out with the help of the MATLAB program and the results are analyzed with accuracy, precision, recall, computational time, reliability scalability, and error rate measures like root mean square error, mean square error, and correlation coefficients. …”
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Firefly algorithm-based neural network for GCPV system output prediction: article / Nor Syakila Mohd Zainol Abidin by Mohd Zainol Abidin, Nor Syakila

“…Additionally, the optimal population size, absorption confession, learning algorithm and type of transfer functions in FA were also investigated in this study. …”
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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…In order to evaluate the performance of the EKF learning algorithm, the proposed algorithm validation were analyzed using model validation methods as a checker such as One Step Ahead (OSA) and correlation coefficient (R2). …”
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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…”

K-means clustering and visualizing of significant words prototype for crowdsourced relationship comments / Muhammad Syafiq Mastor by Mastor, Muhammad Syafiq

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Assessing the effect of learning styles on students' performance using neuro fuzzy system / Nur Haziqah Adzreena Nor' Azman and Norasling Mohamad by Nor' Azman, Nur Haziqah Adzreena, Mohamad, Norasling

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Learning analytic framework for students’ academic performance and critical learning pathways by Lyn, Jessica Tan Yen, Goh, Yong Kheng, Lai, An Chow, Ngeow, Yoke Meng

“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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Book recommendation system using content-based filtering / Amalin Aliesya Mohd Azmi by Mohd Azmi, Amalin Aliesya

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Machine Learning in Sports: Identifying Potential Archers by Rabiu Muazu, Musa, Zahari, Taha, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah

“…This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. …”
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The development of a tracking algorithm for ambulance detection using squaring of RGB and HSV color processing techniques by Mohammad Syawaludin Syafiq, Hassan

“…In this study, a tracking algorithm is developed by means of image processing technique in detecting ambulance. …”
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Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms by Lai V., Ahmed A.N., Malek M.A., Afan H.A., Ibrahim R.K., El-Shafie A., El-Shafie A.

Analysis Of Human Detection Method In Social Distancing Monitoring by Nur Aina Syafinaz, Muhamad Atfan

“…The proposed method for human detection in social distancing monitoring is by using a deep learning algorithm which is You Only Look Once (YOLO) version 3 with custom datasets. …”
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Sedentary sitting posture recognition with YOLOv3 algorithm / Muhammad Amin Mohamad Razali by Mohamad Razali, Muhammad Amin

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Lightning Fault Classification for Transmission Line Using Support Vector Machine by Asman S.H., Aziz N.F.A., Kadir M.Z.A.A., Amirulddin U.A.U., Roslan N., Elsanabary A.

“…The proposed method was implemented in the MATLAB/SIMULINK programming platform. The classification performance of the developed algorithms was evaluated using confusion matrix. …”

Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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