Search Results - evolution ((((computing techniques) OR (estimation techniques))) OR (learning techniques))

Accelerator-based human activity recognition using voting technique with NBTree and MLP classifiers by Azmi M.S.M., Sulaiman M.N.

“…In this study, an accelerator-based activity recognition model using voting technique was proposed. Two machine learning classifiers, Naive Bayes Tree (NBTree) and Multilayer Perceptron (MLP), were used as ensemble classifiers in the voting technique. …”

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

“…Thus, it can be employed as a proficient technique to accurately estimate the state of charge (SOC) of electric vehicle batteries.…”
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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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LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

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Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

“…An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. The first level searches for the appropriate model order while the second level computes the optimal/sub-optimal corresponding parameters. …”
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Modeling 2D appearance evolution for 3D object categorization by Mohd Zaki, Hasan Firdaus, Shafait, Faisal, Mian, Ajmal

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Critical review of object detection techniques for traffic light detection in intelligent transportation systems by Muhammad Adhwa, Mohd Salemi, Muhammad Arif, Mohamad

“…This study provides a critical review of object detection techniques specifically for traffic light detection, evaluating the evolution of machine learning frameworks, deep learning architectures, and hybrid optimization models. …”
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Review of adaptive cell selection techniques in LTE-advanced heterogeneous networks by Gadam, M. A., Abdulazeez Ahmed, Maryam, Ng, Chee Kyun, Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

“…Moreover, more accurate cell load estimation is obtained in the extended RBUR adaptive CRE bias technique through constant bit rate (CBR) traffic, which further improved load balancing as against the estimation based on the number of user equipment (UE). …”
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Assistive Technology For Disabilities: A Case Study Of Autism In Teaching And Learning Outcomes by Omar, Sarah, Bidin, Azman, Koo, Ah Choo

“…A number of studies have highlighted new teaching techniques. There has been a trend in moving towards e-learning technologies in (Agarwal, 2012) and (Kemp, 2015), where those strategies were part of pedagogy techniques in teaching children with special needs. …”
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Email spam classification based on deep learning methods: A review by Tusher, Ekramul Haque, Mohd Arfian, Ismail, Anis Farihan, Mat Raffei

“…Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. …”
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Optimizing railway safety by analyzing human reliability techniques - A review by M. E., M. Aliza, Ahmad Fitri, Yusop, Mohd Adnin, Hamidi, Muhammad Azri, Muhammed Nor

“…This review provides a comprehensive analysis of the evolution of HRA, from the first-generation techniques to the third-generation approaches currently in use. …”
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…Addressing these OBL limitations, this research proposes a new general OBL technique inspired by a natural phenomenon of parallel mirrors systems called the Parallel Mirrors Technique (PMT). …”
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Navigating challenges and opportunities of machine learning in hydrogen catalysis and production processes: Beyond algorithm development by Salehmin M.N.I., Tiong S.K., Mohamed H., Umar D.A., Yu K.L., Ong H.C., Nomanbhay S., Lim S.S.

“…This review uniquely focuses on harnessing the synergy between ML and computational modeling (CM) or optimization tools, as well as integrating multiple ML techniques with CM, for the synthesis of diverse hydrogen evolution reaction (HER) catalysts and various hydrogen production processes (HPPs). …”

The prognostic and predictive modelling of mortality among acute stroke patients in peninsular Malaysia by Nawi, Che Muhammad Nur Hidayat Che

“…Conclusion: Machine learning techniques are increasingly adopted in stroke research, facilitated by global collaborations and advancements in computational science. …”
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Concept Drift Evolution In Machine Learning Approaches: A Systematic Literature Review by Hashmani, M.A., Jameel, S.M., Rehman, M., Inoue, A.

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A New Hybrid K-Means Evolving Spiking Neural Network Model Based on Differential Evolution by Abdulrazak Yahya, Saleh, Haza Nuzly, Abdull Hamed, Siti Mariyam, Shamsuddin, Ashraf, Osman Ibrahim

“…Clustering is one of the essential unsupervised learning techniques in Data Mining. In this paper, a new hybrid (K-DESNN) approach to combine differential evolution and K-means evolving spiking neural network model (K-means ESNN) for clustering problems has been proposed. …”
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Lattice Imperfections in Intermetallic Ti-Al alloys: an X-Ray Diffraction study of the microstructure by the Rietveld method by Lee Liu Mei

“…The analysis also considers the quantitative estimation of different phases and lattice defect related features of the evoluted microstructures, namely crystallite sizes and microstrains in the bulk homogenized state. …”
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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.…”
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Japanese computer-aided learning package / Siti Nur Hidayah Johar by Siti Nur Hidayah , Johar

“…NihonGo was developed using incremental evolution through rapid prototyping technique. The development tool used include Visual Basic.NET, Microsoft Access 2003, Adobe Photoshop CS, and Macromedia Flash MX 2004 and so on. …”
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Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review by Zulkifli, Mansor, Irawan, Addie, Mohammad Fadhil, Abas

“…The analysis encompasses optimization techniques, sensor integration, machine learning, and adaptive control methods, evaluating their impact on robot capabilities. …”
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