Search Results - (( patterns using algorithm ) OR ((( based learning algorithm ) OR ( self learning algorithm ))))

BIOLOGICAL INSPIRED INTRUSION PREVENTION AND SELF-HEALING SYSTEM FOR CRITICAL SERVICES NETWORK by MOHAMED AHMED ELSHEIK, MUNA ELSADIG

“…The design features of the proposed system are inspired by the human immune system, integrated with pattern recognition nonlinear classification algorithm and machine learning. …”
Get full text
Get full text

Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
Get full text
Get full text
Get full text

Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir by Amir, Nur Hazirah

“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
Get full text
Get full text

Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

“…This study aimed to determine the spatiotemporal pattern of the water quality data and identifying the sources of pollution in the Klang River Basin. The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
Get full text
Get full text
Get full text

Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

“…Classification is one of the most active research and application areas of neural networks. Self-organizing map (SOM) is a feed-forward neural network approach that uses an unsupervised learning algorithm has shown a particular ability for solving the problem of classification in pattern recognition. …”
Get full text
Get full text

An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

“…However, these algorithms often fall short in consistently detecting and classifying network intrusions, particularly when distinctions between classes are subtle or when facing evolving attack patterns. …”
Get full text
Get full text
Get full text

Development of spike train algorithms for physiotherapy assessment using deep learning approaches by Nor Rashid, Fadilla' Atyka

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

Development of web based learning content of animation algorithm on searching and sorting techniques / Nur Linda Abdi Nur by Abdi Nur, Nur Linda

“…The objectives of this project is to develop self-learning environment in learning searching and sorting algorithm, enhance understanding of student in learning searching and sorting technique and to apply web-based learning in computer science subject, which focus on courses that use searching and sorting algorithm.…”
Get full text
Get full text

Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…With the goal of enhancing the autonomy in mobile robot navigation, numerous algorithms (traditional AI-based, swarm intelligence-based, self-learning-based) have been built and implemented independently, and also in blended manners. …”
Get full text
Get full text
Get full text
Get full text
Get full text

EEG-based fatigue detection using binary pattern analysis and KNN algorithm by Abd Rahman, Faridah, Roslizan, Iszan Uwais Amer, Gunawan, Teddy Surya, Fitriawan, Helmy, Kartiwi, Mira, Habaebi, Mohamed Hadi

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

Computer-aided system for extending the performance of diabetes analysis and prediction by Murad, Saydul Akbar, Zafril Rizal, M Azmi, Zaid Hafiz, Hakami, Prottasha, Nusrat Jahan, Kowsher, Md

“…The machine learning algorithms used to predict the risks of Type 2 diabetes. …”
Get full text
Get full text
Get full text
Get full text

Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

“…To address this issue, this study incorporated joint graph learning from the gmc algorithm into swmcan, creating a new algorithm called swmcan-jg. …”
Get full text
Get full text

Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

“…These chatbots acquired its intelligence through a hybrid approach that combines pattern-matching technique and machine learning algorithm in order to formulate its responses. …”
Get full text
Get full text

The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
Get full text
Get full text
Get full text
Get full text

Q-Learning-based detection of IPv6 intrusions: a behavioral and performance study by Daru, April Firman, Hirzan, Alauddin Maulana, Mahmod Attar Bashi, Zainab Senan, Fanani, Fajriannoor

“…To address this limitation, the present study proposes a self-learning model using reinforcement learning techniques, specifically the Q-Learning algorithm, to classify network intrusions based on learned behavioural patterns autonomously. …”
Get full text
Get full text
Get full text
Get full text

Optimisation of fed-batch fermentation process using deep reinforcement learning by Chai, Wan Ying

“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
Get full text
Get full text
Get full text

Self-organizing map approach for determining mobile user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Nuraini, Asma, Amin, Sulafa Mohd

“…This paper describes a study towards user location system based on Kohonen Self-Organizing Maps (SOM) algorithm for locating user location with the existing Wi-Fi signals. …”
Get full text
Get full text
Get full text

Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

Subjects:

An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
Get full text
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