Search Results - (( data implication optimisation algorithm ) OR ( wave optimization means algorithm ))
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction
Published 2021“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm
Published 2018“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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Not seeing the forest for the trees: Generalised linear model out-performs random forest in species distribution modelling for Southeast Asian felids
Published 2023“…Our results have strong implications for SDM development, revealing the inconsistencies introduced by the choice of algorithm on scale optimisation, with GLM selecting broader scales than RF.…”
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Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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Hydraulic characterization of PVC-O pipes by means of transient tests
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Smart site monitoring system / Muhammad Azmi and Muhammad Naim Mahyuddin
Published 2023“…These devices collect and transmit data to a centralised cloud-based platform. Advanced data analytics and machine learning algorithms process this data, enabling the system to detect potential safety hazards, monitor construction progress, and predict resource requirements. …”
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Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Optimization of flood inundation simulation using multi-resolution Digital elevation model
Published 2022“…This is due to the limitation of diffusive wave algorithm, 2-dimensional model and effect of grid configuration. …”
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Characterization of oil palm fruitlets using artificial neural network
Published 2014“…The results also showed that contrary to the widely reported gap between the accuracy of the LM algorithm and other feed forward neural network training algorithms, the RP trained network performed as good as that of the LM algorithm for the range of data considered. …”
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Global warming: predicting OPEC carbon dioxide emissions from petroleum consumption using neural network and hybrid cuckoo search algorithm
Published 2015“…To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. …”
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Triple nonlinear hyperbolic PID with static friction compensation for precise positioning of a servo pneumatic actuator
Published 2023“…Although the FSS model caters to friction compensation, optimizing the FSS parameter by applying artificial intelligence, such as Neural Networks (NN) and Genetic Algorithm (GA), will increase the friction modeling‘s accuracy, and improve the compensation…”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Two sets of real-time data are presented in this work. The first one is related to the questionnaire data, consisting of 262 respondent samples, while the second set has 263 samples of pedestrian walking signals. …”
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Framework for pedestrian walking behaviour recognition to minimize road accident
Published 2021“…Two sets of real-time data are presented in this work. The first one is related to the questionnaire data, consisting of 262 respondent samples, while the second set has 263 samples of pedestrian walking signals. …”
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