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81
Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network
Published 2024“…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …”
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82
Use data Mining Techniques to Predict Users’ Engagement on the Social Network Posts in The Period Before, During and After Ramadan
Published 2017“…In contrast to traditional approaches on this topic, this dissertation seeks to analyze the depth of users’ engagement with social media posts and discuss the basis for a predictive model that to predict the total engagement of a post before publishing. At the beginning, a data set was collected from Crowdbabble online tool and the collected dataset presented different periods and different social media networks to examine the user behavior at different times. …”
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83
Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Gradient-Based Optimizer (GBO): A Review, Theory, Variants, and Applications
Published 2023“…This review introduces set of related works of GBO where distributed into; GBO variants, GBO applications, and evaluate the efficiency of GBO compared with other metaheuristic algorithms. …”
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86
Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy
Published 2023“…The trained MLPNN by the LM algorithm predicts 239 laboratory-measured data sets about the methanol (MeOH) loss with the absolute average relative deviation of 6.4% and regression coefficient of 0.9643. …”
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87
A Hybrid Intrusion Detection Model Using EGA-PSO and Improved Random Forest Method
Published 2022“…In the initial phase, the proposed HNIDS utilizes hybrid EGA-PSO methods to enhance the minor data samples and thus produce a balanced data set to learn the sample attributes of small samples more accurately. …”
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88
An Adapted Load-Balancing implementation for Sharded Blockchains
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89
Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels
Published 2023“…The results show that despite using the same data and algorithm, varying the number of personas strongly biases the information system’s personification of the user population. …”
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90
A parallel ant colony optimization to globally optimize area in high-level synthesis. (c2011)
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91
A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation
Published 2021“…The performance of the proposed IRKPCA-RF approach is assessed using a set of emulated data of a grid-tied PV system operating under healthy and faulty conditions. …”
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Acoustic Based Localization of Partial Discharge Inside Oil-Filled Transformers
Published 2022“…<p dir="ltr">This paper addresses the localization of Partial Discharge through a 3D Finite Element Method analysis of acoustic wave propagation inside a 3-phase 35kV transformer with the help of COMSOL Multiphysics software. …”
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94
Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…Our research processes and workflows supported by AI utilize machine learning technology in order to interpret big data, analyze broad data sets and recognize associations with more reliably. …”
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95
From low-cost sensors to high-quality data: A summary of challenges and best practices for effectively calibrating low-cost particulate matter mass sensors
Published 2021“…We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.…”
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96
Nonlinear analysis of shell structures using image processing and machine learning
Published 2023“…The proposed approach can be significantly more efficient than training a machine learning algorithm using the raw numerical data. To evaluate the proposed method, two different structures are assessed where the training data is created using nonlinear finite element analysis. …”
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97
Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
Published 2022“…Our experimental results on four benchmark datasets conclusively demonstrate that the proposed algorithm makes accurate recommendations in item cold-start settings compared to the state-of-the-art algorithms according to commonly used ranking metrics like Normalized Discounted Cumulative Gain (NDCG) and Mean Average Precision (MAP). …”
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Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. …”
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100
A pragmatic approach for testing robustness on real-time component based systems
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