Search Results - (( root active learning algorithm ) OR ( java implication based algorithm ))

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

Get full text
Get full text
Get full text

Time series predictive analysis based on hybridization of meta-heuristic algorithms by Mustaffa, Zuriani, Sulaiman, Mohd Herwan, Rohidin, Dede, Ernawan, Ferda, Kasim, Shahreen

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
Get full text
Get full text

Air quality prediction by machine learning models: A predictive study on the indian coastal city of Visakhapatnam by Ravindiran G., Hayder G., Kanagarathinam K., Alagumalai A., Sonne C.

“…Moreover, by leveraging historical data and machine learning algorithms enables accurate predictions of future urban air quality levels on a global scale. � 2023 The Authors…”

Time series predictive analysis based on hybridization of meta-heuristic algorithms by Zuriani, Mustaffa, M. H., Sulaiman, Rohidin, Dede, Ernawan, Ferda, Shahreen, Kasim

“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
Get full text
Get full text
Get full text

Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman by Nor Adzman, Nurul Khairaini

“…The performance of ANN model was tested using different algorithm and activation function. The number of neuron has been varied from 1-20 while the momentum rate and the learning rate varies from 0.05 until 1. …”
Get full text
Get full text

Output prediction of grid-connected photovoltaic system using artificial neural network: article / Nurul Khairaini Nor Adzman by Nor Adzman, Nurul Khairaini

“…The performance of ANN model was tested using different algorithm and activation function. The number of neuron has been varied from 1-20 while the momentum rate and the learning rate varies from 0.05 until 1. …”
Get full text
Get full text

Forecasting Stock Price by Using Artificial Neural Networks by Nur’azra Alia Nisa, Zulpakar

“…There have been a number of studies conducted on the topic of forecasting stock values using machine learning. Hence, in this study, an Artificial Neural Network model is proposed as a machine learning algorithm for forecasting stock prices. …”
Get full text
Get full text
Get full text

Optimisation of neural network topology for predicting moisture content of spray dried coconut milk powder / Nadiah Syafiqah Shaharuddin, Zalizawati Abdullah and Farah Saleena Taip by Shaharuddin, Nadiah Shafiqah, Abdullah, Zalizawati, Taip, Farah Saleena

“…Based on the result of correlation coefficient of determination (R2) value of 0.9951 and root mean square error (RMSE) value of 0.0145 that was used to evaluate the ANN performance, it can be concluded that the best ANN topology is 2-10-1 with Levenberg-Marquart for learning algorithm, and tangent sigmoid as activation function.…”
Get full text
Get full text
Get full text

Modelling of biogas production process with evolutionary artificial neural network and genetic algorithm by Fakharudin, Abdul Sahli

“…In recent years, several researchers have actively pursued the application of machine learning to biogas production processes. …”
Get full text
Get full text

An ELM-based single input rule module and its application in power generation by Yaw C.T., Wong S.Y., Yap K.S.

“…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”

Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…In addition, ANFIS approach is implemented to predict the �436�45D of wind turbine blades for investigation of algorithms performance based on Coefficient Determination (R2) and Root Mean Square Error (RMSE). …”
Get full text
Get full text
Get full text

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS by FIRAS BASIM, ISMAIL ALNAIMI

“…The encoding and optimization process using genetic algorithms has been applied successfully. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. …”
Get full text
Get full text

An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S. M. M Yassin, S. M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry.The malicious software which is specifically designed to disrupt,damage,or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective.To solve the problem,this paper proposed the integrated machine learning methods consist of J48 and JRip in detecting the malware accurately.The integrated classifier algorithm applied to examine,classify and generate rules of the pattern and program behaviour of system call information.The outcome then revealed the integrated classifier of J48 and JRip outperforming the other classifier with 100% detection of attack rate. …”
Get full text
Get full text
Get full text

An Analysis Of System Calls Using J48 And JRip For Malware Detection by Abdollah, Mohd Faizal, Abdullah, Raihana Syahirah, S.M.M Yassin, S.M. Warusia Mohamed, Selamat, Siti Rahayu, Mohd Saudi, Nur Hidayah

“…The evolution of malware possesses serious threat ever since the concept of malware took root in the technology industry. The malicious software which is specifically designed to disrupt, damage, or gain authorized access to a computer system has made a lot of researchers try to develop a new and better technique to detect malware but it is still inaccurate in distinguishing the malware activities and ineffective. …”
Get full text
Get full text
Get full text

Artificial Neural Network Algorithms to Predict the Compressive Strength of Fly Ash-Based Geopolymers by Siaw Hui, Teo

Get full text
Get full text
Get full text
Get full text

An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

Get full text
Get full text

Shear capacity estimation of reinforced concrete deep beam with vertical bar using artificial neural network and small datasets by Senin, Syahrul Fithry, Mohamad Zamri, Nureen Natasya, Rohim, Rohamezan, Yusuff, Amer, Chan, Hun Beng, Marzuki, Nur Ashikin

“…An optimal network of 11-12 neurons with radial basis activation achieved a training root mean square error (RMSE) of 0.2345. …”
Get full text
Get full text
Get full text

Modeling of Functional Electrical Stimulation (FES): Powered Knee Orthosis (PKO) assisted gait exercise in post-stroke rehabilitation / Adi Izhar Che Ani by Che Ani, Adi Izhar

“…In the human gait model, three Machine Learning algorithms were used: Gaussian Process Regression, Support Vector Machine, and Decision Tree. …”
Get full text
Get full text