Search Results - sampling-((bees algorithm) OR (based algorithm))*

A class skew-insensitive ACO-based decision tree algorithm for imbalanced data sets by Mohd Razali, Muhamad Hasbullah, Saian, Rizauddin, Yap, Bee Wah, Ku-Mahamud, Ku Ruhana

“…This condition impeded the entropy-based heuristic of existing ATM algorithm to develop effective decision boundaries due to its biasness towards the dominant class. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

“…Since it is unrealistic to have a NIRS dataset that can represent unforeseen future changes, an algorithm that can adapt existing data for new samples is worth to be investigated. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights by Seyed Vahid Moravvej, Roohallah Alizadehsani, Sadia Khanam, Zahra Sobhaninia, Afshin Shoeibi, Fahime Khozeimeh, Zahra Alizadeh Sani, Ru-San Tan, Abbas Khosravi, Saeid Nahavandi, Nahrizul Adib Kadri, N. Arunkumar, U.Rajendra Acharya, Muhammad Mokhzaini Azizan

Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Optimisation of Surface Roughness in 3D Printing Using the Bees Algorithm by Kamaruddin, Shafie, Ridzuan, Arman Hilmi, Sukindar, Nor Aiman

“…The result also shows that the Bees Algorithm found a better combination of parameters compared to other algorithms. …”
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Artificial Bee Colony Algorithm for Pairwise Test Generation by Alazzawi, Ammar K., Homaid, Ameen A. Ba, Alomoush, Alaa A., Alsewari, Abdulrahman A.

“…PABC progresses as a means to achieve the effective use of the artificial bee colony algorithm for pairwise testing reduction.…”
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ZigBee environment for indoor localization by Chieh K.S., Keong N.Y., Burhan M.F., Balasubramaniam N., Din N.M.

A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning by Khaksar, Weria, Tang, Sai Hong, Khaksar, Mansoor, Motlagh, Omid Reza Esmaeili

“…Furthermore, the proposed planner is able to solve difficult motion planning instances, including narrow passages and bug traps, which represent particularly difficult tasks for classic sampling-based algorithms. For measuring the uniformity of the generated samples, a new algorithm was created to measure the dispersion of a set of samples based on a predetermined resolution.…”
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Latin hypercube sampling Jaya algorithm based strategy for T-way test suite generation by Nasser, Abdullah B., Abdul-Qawy, Antar S. H., Abdullah, Nibras, Hujainah, Fadhl, Kamal Z., Zamli, Ghanem, Waheed A. H. M.

“…However, losing the search's diversity is a common issue in the metaheuristic algorithm. In order to enhance JA's diversity, enhanced Jaya Algorithm strategy called Latin Hypercube Sampling Jaya Algorithm (LHS-JA) for Test Suite Generation is proposed. …”
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Artificial Bee Colony With Differential Evolution Algorithm For Feature Extraction And Selection Of Mass Spectrometry Data by Mohamed Yusoff, Syarifah Adilah

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A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning by Khaksar W., Hong T.S., Khaksar M., Motlagh O.

Subjects:

Runtime reduction in optimal multi-query sampling-based motion planning by Khaksar W., Sahari K.S.B.M., Ismail F.B., Yousefi M., Ali M.A.

“…Algorithms; Dispersions; Manufacture; Query processing; Robotics; High-dimensional; Low dispersions; Optimal solutions; Path length; Planning tasks; Sampling-based; Sampling-based algorithms; Sampling-based motion planning; Motion planning…”

Statistical Based Real-Time Selective Herbicide Weed Classifier by Ahmed, Irshad, Abdul Muhamin , Naeem, Muhammad, Islam, Azween, Abdullah

“…This paper deals with the development of an algorithm for real time specific weed recognition system based on Sample Variance of an image that is used for the weed classification and comparison of its result with the algorithm based on population variance. …”
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Application of sampling-based motion planning algorithms in autonomous vehicle navigation by Khaksar, Weria, Mohamed Sahari, Khairul Salleh, Tang, Sai Hong

“…In this chapter, a novel sampling-based navigation architecture is introduced, which employs the optimal properties of RRT* planner and the low running time property of low-dispersion sampling-based algorithms. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

“…Although several extensions of the sampling-based algorithms have been proposed for solving each drawback, but the lack of a randomized planner that overcomes abovementioned inefficiencies in a single package is evident and makes the sampling-based path planning less effective for certain purposes. …”
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A new technique for improving the dispersion of a set of samples. Application in multi-query motion planning by Khaksar W., Hong T.S., Sahari K.S.B.M., Khaksar M.

“…For measuring the uniformity of the generated samples, a new algorithm was created to measure the dispersion of a set of samples based on any desired resolution. …”

Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar W., Hong T.S., Sahari K.S.M., Khaksar M., Torresen J.

“…Adaptive control systems; Controllers; Fuzzy neural networks; Fuzzy systems; Motion planning; Robot programming; Robots; Tabu search; Adaptive neuro fuzzy inference systems (ANFIS); Adaptive neuro-fuzzy inference system; ANFIS; Fuzzy controllers; Motion planning algorithms; Sampling-based algorithms; Sampling-based motion planning; Unknown environments; Fuzzy inference…”

Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF) by Mazlan, Nurul Hidayah

“…The proposed algorithm considered features based on its level of importance where weight given based on number of features involved in the sample. …”
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Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…So far, limited genetic-based clustering ensemble algorithms have been developed. …”
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Sampling-based online motion planning for mobile robots: utilization of Tabu search and adaptive neuro-fuzzy inference system by Khaksar, Weria, Tang, Sai Hong, Mohamed Sahari, Khairul Salleh, Khaksar, Mansoor, Toressen, Jim

“…Despite the proven advantages of sampling-based motion planning algorithms, their inability to handle online navigation tasks and providing low-cost solutions make them less efficient in practice. …”
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