Search alternatives:
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
model algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
coding algorithm » cosine algorithm (Expand Search), colony algorithm (Expand Search), scheduling algorithm (Expand Search)
model algorithm » mould algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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441
Isolating Physical Replacement of Identical IoT Devices Using Machine and Deep Learning Approaches
Published 2021Get full text
doctoralThesis -
442
An Intelligent and Low-Cost Eye-Tracking System for Motorized Wheelchair Control
Published 2020“…Different metrics to quantitatively evaluate the performance of each algorithm in terms of accuracy and latency were computed and overall comparison is presented. …”
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443
Optimal Routing and Scheduling in E-commerce Logistics using Crowdsourcing Strategies
Published 2017Get full text
doctoralThesis -
444
Optimal supercharge scheduling of electric vehicles
Published 2018“…The distributed game-theoretical approach recorded promising results especially when compared to the well-known shortest job first scheduling algorithm. Further, unlike the other approaches, which normally are centralized and suited for offline scheduling, the game-based method is suited for online scheduling since it played at anytime a batch of EVs requests charging services. …”
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445
Coalition game theoretic P2P trading in a distribution network integrity-ensured local energy market
Published 2023“…To do so, a coalition game theoretic-model is adopted to model the mutual trading interactions between participating purchasers and sellers in the LEM, in which energy is purchased/sold at a rate lower/higher than the business-as-usual purchase/sell price while the margin of the LEM operator is locked on. …”
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446
A machine learning approach for localization in cellular environments
Published 2018“…The proposed approach only assumes knowledge of RSS fingerprints of the environment, and does not require knowledge of the cellular base transceiver station (BTS) locations, nor uses any RSS mathematical model. …”
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conferenceObject -
447
Robustness testing of composed real-time systems
Published 2010“…In this paper, we suggest a methodology for testing robustness of Real-Time Component-Based Systems (RTCBS). A RTCBS system is described as a collection of components where each component is modeled as a Timed Input-Output Automaton (TIOA). …”
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448
Prediction the performance of multistage moving bed biological process using artificial neural network (ANN)
Published 2020“…To cope with this difficult task and perform an effective and well-controlled BP operation, an artificial neural network (ANN) algorithm was developed to simulate, model, and control a three-stage (anaerobic/anoxic and MBBR) enhanced nutrient removal biological process (ENR-BP) challenging real wastewater. …”
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449
Optimizing overheating, lighting, and heating energy performances in Canadian school for climate change adaptation: Sensitivity analysis and multi-objective optimization methodolog...
Published 2023“…The calibrated simulation model based on indoor and outdoor measured temperature for a school of interest is used to evaluate the optimization strategies. …”
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450
Investigation of Forming a Framework to shortlist contractors in the tendering phase
Published 2022“…After obtaining the weights of the decision factors, a model using Machine Learning algorithm on Google Colab was written using the Python language. …”
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451
Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Published 2023“…The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. The proposed ANN based algorithm has been used for unswerving petite term forecasting. …”
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452
Assessment of Inventory and Transportation Collaboration in a Logistics Marketplace
Published 2020Get full text
doctoralThesis -
453
Process Mining over Unordered Event Streams
Published 2020“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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454
Vehicular-OBUs-As-On-Demand-Fogs
Published 2020“…Our proposed scheme embeds (1) a Kubeadm based approach for clustering OBUs and enabling on-demand micro-services deployment with the least costs and time using Docker containerization technology, (2) a hybrid multi-layered networking architecture to maintain reachability between the requesting user and available vehicular fog cluster, and (3) a vehicular multi-objective container placement model for producing efficient vehicles selection and services distribution. …”
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455
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456
An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation
Published 2019“…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …”
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457
Energy-aware adaptive compression for mobile devices. (c2009)
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masterThesis -
458
Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort
Published 2023“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”
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459
Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure
Published 2014“…Multivariable structure of any fuzzy rule based system would add complexity when modeling the behavior of the system. …”
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conferenceObject -
460
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…Using 11 OGTT measurements, we have deduced 61 features, which are then assigned a rank and the top ten features are shortlisted using minimum redundancy maximum relevance feature selection algorithm. All possible combinations of the 10 best ranked features were used to generate SVM based prediction models. …”