Search Results - (( variable extraction sensor algorithm ) OR ( changes optimization bat algorithm ))
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Reservoir operation based on evolutionary algorithms and multi-criteria decision-making under climate change and uncertainty
Published 2018“…A hybrid framework (optimization-climate change) was used for reservoir operation and the bat algorithm was used for minimization of irrigation deficit. …”
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Optimal operation of hydropower reservoirs under climate change
Published 2024“…The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. …”
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Optimal operation of hydropower reservoirs under climate change
Published 2023“…The study�s novelty is the adaptive and nonadaptive rule curves for power production using optimization algorithms under the climate change model. …”
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Frequency stabilization in interconnected power system using bat and harmony search algorithm with coordinated controllers
Published 2021“…To enhance the outcome of the proposed 2DOF–TIDN controller, its gain parameters are optimized with the use of a newly designed hybrid bat algorithm-harmony search algorithm (hybrid BA–HSA) technique. …”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm
Published 2020“…We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. …”
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Assessment of energy storage and renewable energy sources-based two-area microgrid system using optimized fractional order controllers
Published 2024“…Simulation results reveal that the AOA-based CFOID-FOPIDN outperforms other existing algorithms, such as particle swarm optimization (PSO), bat algorithm (BAT), moth flame optimization (MFO), and whale optimization algorithm (WOA). …”
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Black widow optimization-based optimal PI-controlled wind turbine emulator
Published 2023“…The performance of the BWOA optimized PI controller is compared with a BAT algorithm, particle swarm optimization, and genetic algorithm optimized PI controller to measure the effectiveness of the proposed control system. …”
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Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems
Published 2024“…The AOA-based 2DOF-TIDN performance is compared to the following algorithms: genetic, Jaya, bat, grasshopper optimization, particle swarm optimization, and moth flame optimization. …”
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Simultaneous controllers for stabilizing the frequency changes in deregulated power system using moth flame optimization
Published 2022“…The performance of MFO-based 2DOF PID-FOPDN is evaluated against Cuckoo search (CS), Bat algorithm (BA), and Teaching learning-based optimization (TLBO) approaches in different contract scenarios of deregulated system. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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11
Frequency deviations stabilizations in restructured power systems using coordinative controllers
Published 2021“…Therefore, distinct FACTS controllers and ultra-capacitor (UC) are integrated into two-area restructured systems for strengthening the tie-line power and frequency. Further, new optimization techniques such as cuckoo search (CS), bat algorithm (BA), moth-flame optimization (MFO) are utilized in this work for investigating the suggested 2DOF controllers and compared their performance in all contracts of restructured systems. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke
Published 2019“…This is further worsen by the use of single sensors modality and machine learning algorithms. …”
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Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study
Published 2019“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
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Google the earth: what's next?
Published 2010“…Technologically, the challenge is to design sensors that exhibit high sensitivity to the parameters of interest while minimizing instrument noise and impacts of other natural variables. …”
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Wavelet based fault tolerant control of induction motor / Khalaf Salloum Gaeid
Published 2012“…The fault detection algorithm identifies the time and location of each fault. …”
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New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Despite the effective proposed GMPPT algorithm, the PSCs reduce the maximum power extraction capability of the PV system heavily due to the activation of bypass diodes. …”
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Oil palm female inflorescences anthesis stages identification using selected emissivities through thermal imaging and Machine Learning
Published 2022“…This research studies different Machine Learning (ML) classification and ensemble techniques for the assessment of the four pollination stages consist of pre-anthesis I, pre-anthesis II, pre-anthesis III, and anthesis using thermal imaging. Different ML algorithms such as Random Forest (RF), k Nearest Neighbor (kNN), Support Vector Machine (SVM), Artificial Neural Network (ANN) as well as an ensemble method are used on data extracted from thermal images collected during infield oil palms pollination stages monitoring. …”
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Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm
Published 2018“…In the first phase, spectral features and structural features were extracted for feature extraction. In the spectral features part, the descriptors include red (R), green (G), blue (B), near-infrared (NIR) digital numbers and a vegetation index (VI) was considered. …”
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