Search Results - (( using evolution learning algorithm ) OR ( basic optimization bat algorithm ))

A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem by Mohd Said, Rahaini, A Aziz, Khairul Azha, Zainal Abidin, Amar Faiz, Mat Jizat, Jessnor Arif, Mohd Khairuddin, Ismail, Widiyanto, Sigit, Abdul Waduth, Mohamed Faisal

“…Each bat in the Bat Algorithm represents a potential solution to the issue, and each dimension in the Bat Algorithm's search space represents one of the basic parameters: skew, focal length, and magnification factor. …”
Get full text
Get full text
Get full text

Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…Baldwinian learning uses learning algorithm to change the fitness landscape, but the solution that is found is not encoded back into genetic string. …”
Get full text
Get full text
Get full text

Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

“…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
Get full text
Get full text

Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. A multilayer feed-forward artificial neural network (ANN) with evolution programming learning algorithm for calculation of voltage stability margins (VSM). …”
Get full text
Get full text

Differential evolution for neural networks learning enhancement by Ismail Wdaa, Abdul Sttar

“…These algorithms have widely been used to optimize the learning mechanism of classifiers, particularly on Artificial Neural Network (ANN) Classifier. …”
Get full text
Get full text
Get full text

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

Subjects:

Novel Multi-swarm Approach for Balancing Exploration and Exploitation in Particle Swarm Optimization by Salih, Sinan Q., Alsewari, Abdulrahman A., Al-Khateeb, Bellal, Mohamad Fadli, Zolkipli

Get full text
Get full text
Get full text

Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…The proposed algorithm has been evaluated using 24 benchmark functions. …”
Get full text
Get full text

Evolution strategies for evolving artificial neural networks in an arcade game by Tse, Guan Tan, Teo, Jason, Anthony, Patricia

“…The aim of this paper is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward artificial neural networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game called Ms. …”
Get full text
Get full text
Get full text

Modeling 2D appearance evolution for 3D object categorization by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

“…The parameters learned during this process are used as the 3D shape representations. …”
Get full text
Get full text
Get full text
Get full text

An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection by Ayodele Nojeem, Lasisi

“…These randomly generated detectors suffer from not been able to adequately cover the non-self space, which diminishes the detection performance of the V-Detectors algorithm. This research therefore proposed CSDE-V-Detectors which entail the use of the hybridization of Cuckoo Search (CS) and Differential Evolution (DE) in optimizing the random detectors of the V-Detectors. …”
Get full text
Get full text
Get full text
Get full text

A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
Get full text
Get full text

Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
Get full text
Get full text
Get full text

Improved whale optimization algorithm for feature selection in Arabic sentiment analysis by Tubishat, Mohammad, Abushariah, Mohammad A.M., Idris, Norisma, Aljarah, Ibrahim

“…The proposed algorithm is compared with six well-known optimization algorithms and two deep learning algorithms. …”
Get full text
Get full text

Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
Get full text
Get full text
Get full text
Get full text

An adaptive HMM based approach for improving e-Learning methods by Deeb B., Hassan Z., Beseiso M.

“…Both techniques are used to devise an adaptive algorithm which efficiently manages the clustering of students based on their VAK aptitudes and predicts the future e-learning framework for these students. …”

Machine learning and deep learning approaches for cybersecurity: a review by Halbouni, Asmaa Hani, Gunawan, Teddy Surya, Habaebi, Mohamed Hadi, Halbouni, Murad, Kartiwi, Mira, Ahmad, Robiah

“…This paper reviewed intrusion detection systems and discussed what types of learning algorithms machine learning and deep learning are using to protect data from malicious behavior. …”
Get full text
Get full text
Get full text
Get full text

A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim, Mohd Saad, Norhashimah

“…The proposed method is validated with ten benchmark datasets from UCI machine learning repository. To examine the effectiveness of proposed method, four recent and popular feature selection methods namely BPSO, genetic algorithm (GA), binary gravitational search algorithm (BGSA) and competitive binary grey wolf optimizer (CBGWO) are used in a performance comparison. …”
Get full text
Get full text
Get full text

Nature-Inspired cognitive evolution to play Ms. Pac-Man by Tse, Guan Tan, Jason Teo, Patricia Anthony

“…Some approaches have reported that it is able to solve dynamic problems and very useful for improving the performance of various complex systems. …”
Get full text
Get full text
Get full text