Search Results - (( data location method algorithm ) OR ( parameter evaluation method algorithm ))

Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review by Uddin, Mueen, Darabidarabkhani, Yasaman, Shah, Asadullah, Memon, Jamshed

“…The three algorithms are evaluated for performance using three parameters; power efficiency, cost effectiveness, and amount of CO2 emissions. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Improved criteria determination of an automated negative lightning return strokes characterisation using Brute-Force search algorithm by Abdul Haris, Faranadia

“…A total of 206 negative lightning return strokes waveforms were analysed and automatically characterised using the proposed algorithm. Comparisons of different data, including the manual data (i.e. obtained through the conventional method), data (automated) from a previous study, and the automated data (i.e. obtained using the proposed algorithm), were also carried out by evaluating the percentage difference, arithmetic mean, and standard deviation. …”
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An improved marine predators algorithm tuned data-driven multiple-node hormone regulation neuroendocrine-PID controller for multi-input–multi-output gantry crane system by Mohd Zaidi, Mohd Tumari, Mohd Ashraf, Ahmad, Mohd Helmi, Suid, Mohd Riduwan, Ghazali, M Osman, Tokhi

“…Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.…”
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Evaluation of lightning return stroke current using measured electromagnetic fields by Mahdi, Izadi

“…The proposed algorithm is applied to the measured electric fields’ data from the natural lightning channel while the radial distance is determined using the lightning location system and the simulated electric field using predicted current parameters which are then compared with the measured electric field.…”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks by Han, Fengrong

“…The localization accuracy and robustness of comparison indicated that the developed DWGWO-DV-Hop algorithm super outperforms the other classical range-free methods. …”
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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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Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

“…In this task, two neural network algorithms, Recurrent Neural Networks (RNN) and Multi-Layer Perceptron Neural Networks (MLP-NN) were used and the hyper-parameters of the network architecture was optimized based on a systematic grid search. …”
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Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…Monthly historical rainfall data, antecedent river flow data and meteorology parameters data for two different rivers were used as the input to the proposed models. …”

Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation by Ahmadipour, Masoud

“…The error measurements of the proposed method such as Mean Absolute Percentage Error, Mean Absolute Error, And Root Mean Square Error for islanding detection are less than 0.02% for ideal and noisy conditions which shows that the algorithm is not sensitive to noise. …”
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Analysis of WiMAX Positioning Using Received- Signal-Strength Method by Awang Md Isa, Azmi, Mohamad Isa, Mohd Sa'ari, Mohd Zin, Mohd Shahril Izuan, Haron, Nor Zaidi, Ja'afar, Abd Shukur

“…With this simulator, the user can specify their own data or parameters in analyzing and obtaining the target object location. …”
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Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia by Lay, Usman Salihu

“…Other determinants were velocity and rheological parameters data that is influencing debris flows run-out. …”
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EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

“…The IncFRNN technique was evaluated using a collected EEG data from 37 subjects. …”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada by Barham, A., Ismail, M.S., Hermana, M., Padmanabhan, E., Baashar, Y., Sabir, O.

“…Total Organic Carbon (TOC) and maturity level (Tmax) for any source rock considered to be the key parameters for evaluating its potentiality. The TOC and Tmax are estimated mainly by analyzing core samples or cuttings using the common nonfilter acidification combustion and pyrolysis, both methods are time-consuming and costly. …”
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Application of Machine Learning and Deep Learning Algorithms for Landslide Susceptibility Assessment in Landslide Prone Himalayan Region by Bhattacharya S., Ali T., Chakravortti S., Pal T., Majee B.K., Mondal A., Pande C.B., Bilal M., Rahman M.T., Chakrabortty R.

“…Effective planning and management of these locations are essential. In recent years, statistical methods and, increasingly, machine learning-based approaches have gained popularity for landslide susceptibility modeling. …”

Predicting the maturity and organic richness using artificial neural networks (ANNs): A case study of Montney Formation, NE British Columbia, Canada by Barham A., Ismail M.S., Hermana M., Padmanabhan E., Baashar Y., Sabir O.

A Study on Performance Comparisons between KNN, Random Forest and XGBoost in Prediction of Landslide Susceptibility in Kota Kinabalu, Malaysia by Soo See, Chai, Dorothy, Martin

“…The research areas had 242 landslide locations, and the inventory data was arbitrarily separated into training and testing datasets in a 7/3 ratio. …”
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Developing an ensembled machine learning model for predicting water quality index in Johor River Basin by Sidek L.M., Mohiyaden H.A., Marufuzzaman M., Noh N.S.M., Heddam S., Ehteram M., Kisi O., Sammen S.S.

“…Then, in terms of WQI calculation, feature importance method is used to identify the most important parameters that can be used to predict the WQI. …”