Search Results - (( wave adaptation optimization algorithm ) OR ( code classification tree algorithm ))

Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
Get full text
Get full text

Water wave optimization with deep learning driven smart grid stability prediction by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, Alamgeer, Mohammad, K. Nour, Mohamed, Abdelrahman, Anas, Motwakel, Abdelwahed

“…In this background, the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction (WWOODL-SGSP) model. …”
Get full text
Get full text
Get full text

Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

“…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
Get full text
Get full text
Get full text
Get full text

CUDA implementation of fractal image compression by Al Sideiri A., Alzeidi N., Al Hammoshi M., Chauhan M.S., AlFarsi G.

Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

“…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
Get full text
Get full text
Get full text

Comparative analysis for topic classification in juz Al-Baqarah by Rahman, Mohamad Izzuddin, Samsudin, Noor Azah, Mustapha, Aida, Abdullahi Oyekunle, Adeleke

“…The SVM performance is then compared against other classification algorithms such as Naive Bayes, J48 Decision Tree and K-Nearest Neighbours. …”
Get full text
Get full text

Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…Thus, we propose an adaptive multi-parent crossover Genetic Algorithm (GA) for optimizing the features used in classifying epileptic seizures. …”
Get full text
Get full text

Cybernetics approaches in intelligent systems for crops disease detection with the aid of IoT by Rathinam R., Kasinathan P., Govindarajan U., Ramachandaramurthy V.K., Subramaniam U., Garrido S.

Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

“…To further validate the generalization accuracy of the LSB_ANN, its performance was compared with that of a Multi-ANFIS network as well as those of three different ANN training algorithms: Levenberg Marquardt (LM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA). …”
Get full text
Get full text

Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
Get full text
Get full text

Handover Parameter for Self-optimisation in 6g Mobile Networks: A Survey by Ukasyah Mahamod, Ibraheem Shayea, Hafizal Mohamad, Marinah Othman, Fauzun Abdullah Asuhaimi

Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

Get full text
Get full text

VHF adaptive antenna using a rear defogger by Abdullah, Noorsaliza

“…Downhill simplex method is used as an algorithm to form the adaptive beam for the proposed antenna. …”
Get full text
Get full text

Wearable based-sensor fall detection system using machine learning algorithm by Ishak, Anis Nadia, Habaebi, Mohamed Hadi, Yusoff, Siti Hajar, Islam, Md. Rafiqul

“…As for future work, the plan is to convert the code to an app to run on the smartphone so it can be commercialized.…”
Get full text
Get full text
Get full text
Get full text
Get full text

Energy-efficient power allocation for downlink non orthogonal multiple access networks based on game theory and genetic algorithm / Reem Mustafa Mah’d Al Debes by Reem Mustafa , Mah’d Al Debes

“…Furthermore, the research explores advanced applications such as integrating NOMA with Millimeter-Wave technology and optimizing user association strategies, enhancing system capacity and overall performance. …”
Get full text
Get full text
Get full text

XAIRF-WFP: a novel XAI-based random forest classifier for advanced email spam detection by Bouke, Mohamed Aly, Alramli, Omar Imhemed, Abdullah, Azizol

Get full text
Get full text
Get full text

Computational electromagnetic modeling and optimization techniques to enhance the accuracy and efficiency of a 2.45 GHz pyramidal horn antenna by Newton-Raphson method for IEMI tes... by Hamamah, Fuad, Ahmad, Wfh F.H.W., Gomes, C., Mohd Isa, M., Homam, M. J.

“…Using CST Microwave Studio and optimization techniques, the return losses for the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Interior Point Quadratic Newton (IPQN), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) were-29.61dB,-30.45dB,-26.2dB, and-30.24dB, respectively. …”
Get full text
Get full text

Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

“…This is realized by artificially generating canceling (secondary) source(s) of sound through detecting the unwanted (primary) noise and processing it by an electronic controller, so that when the secondary wave is superimposed on the primary wave the two destructively interfere and cancellation occurs at the observation point. …”
Get full text
Get full text