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models algorithm » mould algorithm (Expand Search), deer algorithm (Expand Search)
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settings » setting (Expand Search)
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…Features extracted from the proposed BoDF model have considerably smaller dimensions. The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. …”
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383
Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition
Published 2019“…In this paper, we introduce a new algorithmic framework for autonomous music sentiment-based expression and composition, titled MUSEC, that perceives an extensible set of six primary human emotions (e.g., anger, fear, joy, love, sadness, and surprise) expressed by a MIDI musical file and then composes (creates) new polyphonic (pseudo) thematic, and diversified musical pieces that express these emotions. …”
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384
A Fusion-Based Approach for Skin Cancer Detection Combining Clinical Images, Dermoscopic Images, and Metadata
Published 2025Get full text
doctoralThesis -
385
A hybrid model to predict the pressure gradient for the liquid-liquid flow in both horizontal and inclined pipes for unknown flow patterns
Published 2023“…The achieved MAPE using the proposed hybrid model is superior to existing mechanistic or correlation-based models reported in the literature (between 26 and 69%). …”
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386
A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics
Published 2011“…XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. …”
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387
A Novel Approach for Detecting Anomalous Energy Consumption Based on Micro-Moments and Deep Neural Networks
Published 2022“…This paper introduces a new solution to detect energy consumption anomalies based on extracting micro-moment features using a rule-based model. …”
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388
Loss Model Control for Efficiency Optimization and Advanced Sliding Mode Controllers with Chattering Attenuation for Five-Phase Induction Motor Drive
Published 2024“…<p dir="ltr">This paper proposes firstly a Second Order Sliding Mode Control (SOSMC) based on a Super Twisting Algorithm (STA) (SOSMC-STA) combined with a Direct Field-Oriented Control (DFOC) strategy of a Five-Phase Induction Motor (FPIM). …”
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389
Optimization of Commercially Off the Shelf (COTS) Electric Propulsion System for Low Speed Fuel Cell UAV
Published 2013Get full text
doctoralThesis -
390
Simultaneous analysis of frequency and voltage control of the interconnected hybrid power system in presence of FACTS devices and demand response scheme
Published 2021“…System responses have been critically analyzed under Mine Blast Algorithm (MBA) based proportional–integral–derivative (PID) controllers</p><h2>Other Information</h2><p dir="ltr">Published in: Energy Reports<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.egyr.2021.10.100" target="_blank">https://dx.doi.org/10.1016/j.egyr.2021.10.100</a></p>…”
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Ensemble-Based Spam Detection in Smart Home IoT Devices Time Series Data Using Machine Learning Techniques
Published 2020“…A spamicity score was awarded to each of the IoT devices by the algorithm, based on the feature importance and the root mean square error score of the machine learning models to determine the trustworthiness of the device in the home network. …”
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Ensemble Deep Random Vector Functional Link Neural Network for Regression
Published 2022“…To address this problem, we propose a random skip connection-based edRVFL, which can keep the diversity in the latent space. esc-RVFL is an ensemble scheme that utilizes several edRVFL-RSC models trained on the different folds of the training dataset. …”
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Active distribution network type identification method of high proportion new energy power system based on source-load matching
Published 2023“…Here, we report an active distribution network type identification method based on source-load matching. Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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396
Day-Ahead Load Demand Forecasting in Urban Community Cluster Microgrids Using Machine Learning Methods
Published 2022“…From the results, it is found that the Levenberg–Marquardt optimization algorithm-based ANN model gives the best electrical load forecasting results.…”
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397
A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security
Published 2023“…Moreover, the Reconciliate Multi-Agent Markov Learning (RMML) based classification algorithm is used to predict the intrusion with its appropriate classes. …”
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398
Clustering and Stochastic Simulation Optimization for Outpatient Chemotherapy Appointment Planning and Scheduling
Published 2022“…A Stochastic Discrete Simulation-Based Multi-Objective Optimization (SDSMO) model is developed and linked to clustering algorithms using an iterative sequential approach. …”
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399
Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment
Published 2022“…On the other hand, the transfer learning skills demonstrated in this study indicate that discovering suitable testing models from the ground is also achievable using our model with optimum prior cryptographic expertise, where we contribute the results of deep learning in the field of deep learning based differential cryptanalysis development.Various experiments were performed on discrete and continuous chaotic and non-chaotic permutation patterns, and the best-performing model had an MSE of 1.8217e−04 and an R2 of 1, demonstrating the practicality of the suggested technique.…”
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Could Petrol Stations Play a Key Role in Transportation Electrification? A GIS-Based Coverage Maximization of Fast EV Chargers in Urban Environment
Published 2022“…More specifically, the location problem is modelled as a maximum coverage location problem (MCLP) and solved using a geographic information system (GIS) based platform. …”