Search Results - (( simulation optimization sensor algorithm ) OR ( data optimization bees algorithm ))

A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

“…This creates problem for novice users especially to those who have no or little knowledge on the data.Trial-error attempt might be one of the possible preference to deal with this issue.In this paper, an optimization algorithm inspired from the bees foraging activities is used to locate near-optimal centroid of a given data set.Result shows that propose approached prove it robustness and competence in finding a near optimal centroid on both synthetic and real data sets.…”
Get full text
Get full text
Get full text

Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage by Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz

“…Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. …”
Get full text
Get full text
Get full text

Data clustering using the bees algorithm by Pham, D.T, Otri, S., Afify, A., Mahmuddin, Massudi, Al-Jabbouli, H.

“…The authors’ team have developed a new population based search algorithm called the Bees Algorithm that is capable of locating near optimal solutions efficiently. …”
Get full text
Get full text

Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

“…The paper presents the results obtained to demonstrate the strengths of the Bees Algorithm as an optimization tool.…”
Get full text
Get full text
Get full text

IWDSA: a hybrid Intelligent Water Drops with a Simulated Annealing for the localization improvement in wireless sensor networks by Gumaida, Bassam, Ibrahim, Adamu Abubakar

“…Additionally, simulation results confirm that the proposed algorithm IWDSA exhibits outstanding performance compared to other algorithms utilizing optimization techniques, including genetic algorithms, bat algorithms, ant colony optimization, and swarm optimization. …”
Get full text
Get full text
Get full text

Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
Get full text
Get full text
Get full text

Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data by Hassan, S., Jaafar, J., Khanesar, M.A., Khosravi, A.

“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
Get full text
Get full text

Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification by Al Nuaimi, Zakaria Noor Aldeen Mahmood, Abdullah, Rosni

“…By optimizing the training of the neural networks using optimal weight set, better results can be obtained by the neural networks.Traditional neural networks algorithms such as Back Propagation (BP) were used for ANNT, but they have some drawbacks such as computational complexity and getting trapped in the local minima.Therefore, evolutionary algorithms like the Swarm Intelligence (SI) algorithms have been employed in ANNT to overcome such issues.Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
Get full text
Get full text
Get full text

Surface roughness optimization based on hybrid harmony search and artificial bee colony algorithm in electric discharge machining process by Deris A.M., Solemon B.

Mobile robot path optimization algorithm using vector calculus and mapping of 2 dimensional space by Zahari, Ammar, Ismail , Amelia Ritahani, Desia, Recky

“…The simulated robot is equipped with a sonar sensor and several infrared sensors on its chassis. …”
Get full text
Get full text
Get full text

Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

“…Therefore, test data generation for t-way testing need to be optimized. …”
Get full text
Get full text
Get full text

Binary Artificial Bee Colony Optimization For Weighted Random 2 Satisfiability In Discrete Hopfield Neural Network by Muhammad Sidik, Siti Syatirah

“…The Binary Artificial Bee Colony will be utilized to optimize the logical structure according to the ratio of negative literals by capitalizing the features of the exploration mechanism of the algorithm. …”
Get full text
Get full text

System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm by Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.

Content caching in ICN using Bee-Colony optimization algorithm by Abdullahi, Ibrahim, Che Mohamed Arif, Ahmad Suki, Hassan, Suhaidi

“…Different caching issues has raised concern about the content flooded all over the Internet.In line with the challenges, Bee-Colony Optimization Algorithm (B-COA) has been proposed in this paper to avail content on the Internet with less referral cost and heavy monopoly of data on hosts.It is believed that the advantages of the grouping and waggle phase could be used to place the contents faster in ICN.…”
Get full text
Get full text
Get full text

Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network by Husna, Jamal Abdul Nasir

“…Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. …”
Get full text
Get full text
Get full text
Get full text

Deterministic static sensor node placement in wireless sensor network based on territorial predator scent marking behavior by Abidin H.Z., Din N.M., Radzi N.A.M.

“…This paper proposes a sensor node placement algorithm that utilizes a new biologically inspired optimization algorithm that imitates the behaviour of territorial predators in marking their territories with their odours known as Territorial Predator Scent Marking Algorithm (TPSMA). …”

Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
Get full text
Get full text
Get full text
Get full text

Solving Traveling Salesman’s Problem Using African Buffalo Optimization, Honey Bee Mating Optimization & Lin-Kerninghan Algorithms by Odili, Julius Beneoluchi, M. N. M., Kahar, Noraziah, Ahmad

“…This paper compares the performances of the African Buffalo Optimization (ABO), hybrid Honey Bee Mating Optimization (HBMO) and the Lin-Kernighan (LKH) algorithms for solving the problems of the Symmetric Travelling Salesman’s Problems. …”
Get full text
Get full text
Get full text

Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement by Abidin H.Z., Din N.M.

Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
Get full text
Get full text
Get full text
Get full text