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Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…This paper presents an improved machine learning approach for the accurate and robust state of charge (SOC) in electric vehicle (EV) batteries using differential search optimized random forest regression (RFR) algorithm. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Differential Search Optimized Random Forest Regression Algorithm for State of Charge Estimation in Electric Vehicle Batteries
Published 2023Conference Paper -
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Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm
Published 2020“…However, in this paper, we are not concentrating on the such learning of estimating, confirming or authenticating a Hadith. …”
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Lithium-ion Battery State of Charge Estimation Method Using Optimized Deep Recurrent Neural Network Algorithm
Published 2023Conference Paper -
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Bayesian Network of Traffic Accidents in Malaysia
Published 2019“…By using Hill Climb (HC) and Tabu algorithms, the structure of the data was learnt and their relationship is estimated through the conditional probability based on the Bayes theorem. …”
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A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim
Published 2017“…The results showed that the decision algorithm improves the measurement by 28% and the degraded transcoded video does not affect students' comprehension.…”
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Predicting Diseases Using Multi-BackPropagation
Published 2002“…Multi-network approach does not require any changes in neural network learning algorithm. …”
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A hybrid deep CNN model for fast class-incremental food classification / Aymen Taher Ahmed al-Ashwal
Published 2019“…Lastly, the incremental learning algorithm ABACOC is used to classify each feature of food classes. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Finally, one key drawback of estimating streamflow outlined above is that it does not account for variability. …”
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A direct ensemble classifier for learning imbalanced multiclass data
Published 2013“…The learning framework consists of ensemble learning and decision combiner model with general supervised learning algorithms as base learner. …”
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…In this research, the long-established single-image super-resolution problem is addressed by integrating the multiresolution property of Wavelet and the flexibility of Locally Anchored Neighbourhood Regression model to formulate a novel edgebased single image super resolution algorithm that allows robust estimation of missing frequency details in wavelet domain with complete enhancement procedure. …”
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Application of boundary-fitted convolutional neural network to simulate non-Newtonian fluid flow behavior in eccentric annulus
Published 2022“…The performance of the algorithm is validated with experimental data available from published studies. …”
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EstiCal: food calorie image recognition mobile application by using feature descriptor technique / Muhammad Asyraf Suhaimi
Published 2018“…The future work of the project can be done with additional features such as using a hybrid algorithm which is combining algorithms to improvise the feature descriptor or applying a machine learning technique to increase the efficiency of food recognition.…”
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