Search Results - (( parameter evaluation method algorithm ) OR ( pattern evaluation method algorithm ))

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Chemical Vapor Deposition (CVD) is the most efficient method for CNTs production.However,using CVD method encounters crucial issues such as customization,time and cost.Therefore,Response Surface Methodology (RSM) is proposed for modeling and the ABC-βHC is proposed for optimization purpose to address such issues.The selected CNTs characteristics are CNTs yield and quality represented by the ratio of the relative intensity of the D and G-bands (ID/IG).Six case studies are generated from collected dataset including four cases of CNTs yield and one case of ID/IG as single objective optimization problems,while the sixth case represents multi-objective problem.The input parameters of each case are a subset from the set of input parameters including reaction temperature,duration,carbon dioxide flow rate,methane partial pressure,catalyst loading,polymer weight and catalyst weight.The models for the first three case studies were mentioned in the original work.RSM is proposed to develop polynomial models for the output responses in the other three cases and to identi significant process parameters and interactions that could affect the CNTs output responses.The developed models are validated using t-test,correlation and pattern matching.The predictive results have a good agreement with the actual experimental data.The models are used as objective functions in optimization techniques.For multi-objective optimization,this study proposes Desirability Function Approach (DFA) to be integrated with other proposed algorithms to form hybrid techniques namely RSM-DFA,ABC-DFA and ABC-βHC-DFA.The proposed algorithms and other selected well-known algorithms are evaluated and compared on their CNTs yield and quality.The optimization results reveal that ABC-βHC and ABC-βHC-DFA obtained significant results in terms of success rate,required time,iterations,and function evaluations number compared to other well-known algorithms.Significantly,the optimization results from this study are better than the results from the original work of the collected dataset.…”
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New learning algorithm based on Hidden Markov Model (HMM) as stochastic modelling for pattern calssification by Balakrishnan, Malarvili, Ting, Chee Ming, Shaikh Salleh, Sheikh Hussain

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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Offline handwritten character recognition using backpropagation neural network / Masnizah Mohadi by Mohadi, Masnizah

“…As a result of this project, it is proven that the backpropagation algorithm can be used for recognizing handwritten characters and recognition tasks depends highly on how the data was preprocessed and the network parameter itself.…”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

Seismic attribute feasibility study for fault and fracture analysis and integration with spectral decomposition: Application in Sarawak basin by Hamidi, R., Ghosh, D.

“…However, there are some limitations in the performance of these tools, as the algorithms are dependent on the seismic survey parameters, quality of the data and its existing patterns, and geology of the study area. …”
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Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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Chemometric approaches in the evaluation of trace metals in commercially raised tilapia and preliminary health risk assessment of its consumption / Low Kah Hin by Low, Kah Hin

“…The aims of this study are to evaluate the presence of trace metals in aquacultural samples using chemometric methods and to assess the safety of their consumption. …”
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm by Alyaa Ghazi Mohammed, Mohd Zakree Ahmad Nazri

“…Our in-depth analysis underscores the substantial relevance of the Z-Alizadeh Sani dataset in accurately categorizing heart disease manifestations, with the proposed CAD model achieving a competitive accuracy rate of 86.66% when evaluated on subsets from the UCI repository. This performance is validated through rigorous comparative assessments against various classification algorithms and state-of-the-art methods, revealing notable advantages in terms of predictive precision, computational efficiency, and adaptability to real-world clinical scenarios. …”
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Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

“…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications by Teoh, Ming Xue

“…On the other hand, artificial intelligence had been ways to enhances embedded system by enabling real-time, accurate detection and management of PCB defects through advanced pattern recognition and automated inspection methods. …”
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A comprehensive comparison of recent developed meta-heuristic algorithms for streamflow time series forecasting problem by Ahmed A.N., Van Lam T., Hung N.D., Van Thieu N., Kisi O., El-Shafie A.

Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

“…The results showed that the MCMC algorithm can estimate the parameters of the MA model. …”
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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…Current development in precision agriculture has underscored the role of machine learning in crop yield prediction. Machine learning algorithms are capable of learning linear and nonlinear patterns in complex agro-meteorological data. …”

Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…The developed models were applied to three different case studies to evaluate the performance of the models. The results showed that the proposed model could capture patterns of the monthly and daily interval of the hydrological time series. …”
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Computational dynamic support model for social support assignments around stressed individuals among graduate students by Al-Shorman, Roqia Rateb

“…The algorithm complexity analysis was used to measure the execution time in the worst case. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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