Search Results - intelligence _ ((cell algorithm) OR (((window algorithm) OR (learning algorithm))))

Energy management strategies, control systems, and artificial intelligence-based algorithms development for hydrogen fuel cell-powered vehicles: A review by Oladosu T.L., Pasupuleti J., Kiong T.S., Koh S.P.J., Yusaf T.

“…The multi-objective-based algorithm, reinforcement learning algorithm, and different hybridizations are enhancing HFCEVs cost-competing edge. ? …”

Predicting breast cancer using ant colony optimisation / Siti Sarah Aqilah Che Ani by Che Ani, Siti Sarah Aqilah

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Distributed learning based energy-efficient operations in small cell networks by Mughees, Amna

“…Additionally, an intelligent distributed cooperative power allocation learning algorithm is proposed to enhance energy efficiency in small cell networks while satisfying the scalability, power constraint, user association requirements, and QoS constraints. …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm by Mohamed, M. E, Samir, B. B., Azween, Abdullah

“…A new non classification algorithm was developed based on the danger theory model of human immune system (HIS).The abstract model of system algorithm is inspired from HIS cell mechanism mainly, the Dendritic cell behavior and T-cell mechanisms. …”
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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Design and optimization of a test case generation algorithm for real-time embedded systems based on adaptive Q-Learning by Yingbei, Niu, Chai, Soo See

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Designing a new model for worm response using security metrics by Madihah Mohd Saudi, Taib B.M.

Subjects:

Comparative analysis of danger theory variants in measuring risk level for text spam messages by Zainal K., Jali M.Z., Hasan A.B.

Artificial intelligent power prediction for efficient resource management of WCDMA mobile network by Tee Y.K., Tinng S.K., Koh J., David Y.

“…The output of SVR will be used by WCDMA mobile network to decide on new service admission. Genetic algorithm (GA) is then applied to form optimal beams to cover all UEs in a cell with minimum power. …”

Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

“…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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Hybrid of convolutional neural network algorithm and autoregressive integrated moving average model for skin cancer classification among Malaysian by Chin, Chee Ka, Dayang Azra, Awang Mat, Abdulrazak Yahya, Saleh

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Utilisation of Exponential-Based Resource Allocation and Competition in Artificial Immune Recognition System by Hormozi, Shahram Golzari

“…Next, the Real World Tournament Selection method is adapted and incorporated into the resource competition of Artificial Immune Recognition System. The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…Since the emergence of AIS, it has proved itself as an area of computational intelligence. Real-Valued Negative Selection Algorithm with Variable-Sized Detectors (V-Detectors) is an offspring of AIS and demonstrated its potentials in the field of anomaly detection. …”
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Predictive Analytics Of Cigs Solar Cell Using A Combinational Gra-Mlr-Ga Model by Salehuddin, Fauziyah, Kaharudin, Khairil Ezwan, Mohd Zain, Anis Suhaila, Roslan, Ameer Farhan

“…Nevertheless, the impact of layer thickness and doping concentration of a window layer - Zinc oxide (ZnO), a buffer layer - Cadmium sulfide (Cds) and an absorber layer (CIGS) needs to be intelligently controlled for more balanced CIGS solar cell performances. …”
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Blood cell classification using deep learning by Liaw, Mun Kin

“…The advancement of Artificial Intelligence (AI) has introduced complex methods such as deep learning that would automate the classification of blood cells in a fast and accurate manner Thus, the study of White Blood Cells (WBCs) classification using deep learning techniques is proposed in this research. …”
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On equivalence of FIS and ELM for interpretable rule-based knowledge representation by Wong S.Y., Yap K.S., Yap H.J., Tan S.C., Chang S.W.

“…Classification (of information); Computer aided diagnosis; Fault detection; Fuzzy systems; Knowledge acquisition; Knowledge representation; Learning systems; Matrix algebra; Membership functions; Pattern recognition; Extreme learning machine; Fault detection and diagnosis; Fuzzy if-then rules; Fuzzy inference systems; Fuzzy membership function; Initialization technique; Interpretable rules; Rule based; Fuzzy inference; algorithm; artificial intelligence; artificial neural network; benchmarking; classification; electric power plant; factual database; feedback system; fuzzy logic; machine learning; nerve cell; reproducibility; statistical model; Algorithms; Artificial Intelligence; Benchmarking; Classification; Databases, Factual; Feedback; Fuzzy Logic; Machine Learning; Models, Statistical; Neural Networks (Computer); Neurons; Power Plants; Reproducibility of Results…”

An Intelligent Hybrid Model Using CNN and RNN for Crop Yield Prediction by JUNE, KHOO YAN

“…CNN algorithm is used in this study due to its characteristic where it considers a smaller number of parameters in the network, and it has a lower chance of overfitting While RNN acts as a prediction model in this study. …”
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Hearing disorder detection using auditory evoked potential (AEP) signals by Islam, Md Nahidul, Norizam, Sulaiman, Rashid, Mamunur, Bari, Bifta Sama, Mahfuzah, Mustafa

“…Ten different statistical features have been extracted in ten different time window length (one second to ten seconds). The obtained feature sets have been classified by the K-Nearest Neighbors (K-NN) algorithm. …”
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Designing a New Model for Worm Response Using Security Metrics by Madihah Mohd Saudi, Taib, BM

“…In this model, the static and dynamic analyses were conducted and the machine learning algorithms were applied to optimize the performance. …”

Intelligent signature detection for scanning Internet Worms by Rasheed M.M., Ghazali O., Norwawi N.M.