Search Results - (( java application customization algorithm ) OR ( parameters variation learning algorithm ))
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1
Optimal variational mode decomposition and integrated extreme learning machine for network traffic prediction
Published 2021“…However, most of the existing evolutionary algorithms have some adjustable parameters which depend on subjective experience or prior knowledge. …”
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2
The effect of adaptive parameters on the performance of back propagation
Published 2012“…The results show that the proposed algorithm extensively improves the learning process of conventional Back Propagation algorithm.…”
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Thesis -
3
Optimisation of fed-batch fermentation process using deep reinforcement learning
Published 2023“…Fed-batch fermentation process has always been a challenge for optimisation because it is highly non-linear and complex. Deep reinforcement learning is a self-learning algorithm through trial and error and experience, without any prior knowledge. …”
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4
Data Analysis and Machine Learning Algorithms Evaluation for Bioliq AI-based Predictive Tool
Published 2019“…This final year project identified relevant parameters through literature research, analysis and expert interview, and evaluated different machine learning algorithms and identified linear regression as the most applicable and efficient with its R-square of 0.8015, qualifying it to be used for the development of a hybrid model for the AI-based tool for predictive process optimization for chemical plants.…”
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5
Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms
Published 2022“…A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. …”
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Deep Learning Based Face Attributes Recognition
Published 2018“…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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Monograph -
7
A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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8
Building detection using object-based Image analysis (OBIA) and machine learning (ML) algorithms / Hanani Mohd Shahar
Published 2020“…In order to obtain a good classification accuracy, the suitable segmentation parameters (scale, shape and compactness) and features selection have been determined and Machine learning (ML) algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT) classifiers have been applied to categorized five different classes which are water, forest, green area, building, and road. …”
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9
Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics
Published 2021“…The analysis from machine learning SVR method shows the good predictability of the adsorption in the variation with shale fabric parameters. …”
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10
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…The proposed approach contains several benefits including simple implementation, tolerance of turbine parameter or several nonparametric uncertainties. Robust control of the generator output power with wind-speed variations can also be considered as a big advantage of this strategy.…”
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11
Automatic Segmentation and Classification of Skin Lesions in Dermoscopic Images
Published 2024“…In the third classification algorithm, hybrid features are extracted using AlexNet and VGG-16 through a transfer learning approach where parameter manipulation is implemented to simplify the network. …”
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12
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…Back Propagation (BP) has proven to be a robust algorithm for different connectionist learning problems which commonly available for any functional induction that provides a computationally efficient method. …”
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13
Hybrid OCSSA-VMD and optimized deep learning networks for runoff forecasting
Published 2025“…To improve accuracy and address the non-linearity and non-stationarity in monthly runoff forecasting, this paper proposes a method that integrates intelligent optimization techniques with Deep Learning (DL) network. The Osprey-Cauchy-Sparrow Search Algorithm (OCSSA) is employed to fine-tune the parameters of Variational Mode Decomposition (VMD), which is utilized to break down the original runoff data into multiple Intrinsic Mode Functions (IMFs). …”
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. Two parameters (population size and generation numbers) are adaptively adopted from number of remaining ranking features. …”
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15
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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16
Identification of continuous-time model of hammerstein system using modified multi-verse optimizer
Published 2021“…The statistical analysis value (mean) was taken from the parameter deviation index to see how much our proposed algorithm has improved. …”
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17
Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…EHA are known to have nonlinear parameters and dynamic factors such as frictions, load variations and leakage. …”
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18
Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)
Published 2019“…This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Prediction of Rheological and Filtration Loss Properties of Nano-Zirconium-Dioxide Drilling Fluids via Machine Learning Techniques for Energy Exploration
Published 2025“…The techniques utilized are artificial neural network (ANN) and random forest (RF). Both machine learning algorithms are tuned to acquire the best set of hyper-parameters. …”
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