Search Results - (( data optimization based algorithm ) OR ( data active learning algorithm ))
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1
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…Based on the results obtained, a better prediction result can be produced by the proposed GA-BPNN learning algorithm.…”
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Thesis -
2
Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection
Published 2026“…In the experiment, we conducted an evaluation of the effectiveness and efficiency of four nature-inspired binary algorithms for optimization namely Binary Particle Swarm Optimization (BPSO), Binary Grey Wolf Optimization algorithm (BGWO), Binary Differential Evolution algorithm (BDE), and Binary Salp Swarm algorithm (BSS) - in the context of human activity recognition (HAR). …”
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3
Forecasting of fine particulate matter based on LSTM and optimization algorithm
Published 2024“…The proposed models predict the hourly air pollutant concentration based on 4-h historical input based on six air pollutant data, meteorology parameters, and PM2.5 concentration data from the neighboring air quality monitoring stations. …”
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4
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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5
An evolutionary based features construction methods for data summarization approach
Published 2015“…In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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Research Report -
6
Constrained–Optimization-based Bayesian posterior probability extreme learning machine for pattern classification
Published 2023“…Using random computational hidden neurons, ELM shows faster learning speed over the traditional learning algorithms. …”
Conference Paper -
7
EEG-based emotion recognition using machine learning algorithms
Published 2024“…Training will be conducted so the model can learn and capture patterns of data. Moreover, fine-tuning of model will be applied to get the optimal performance in machine learning model. …”
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Final Year Project / Dissertation / Thesis -
8
A dynamic eLearning prediction modelbased on incomplete activities of eLearning system
Published 2020“…This study was conducted through seven steps: initial study; data collection; data pre-processing; eLearning activity analysis; learning outcome prediction model construction; eLearning prediction model synthesizing; and model evaluation. …”
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9
Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed
Published 2012“…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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10
Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel modified stacked ensemble statistical learning-based algorithm based on potential determinants, following the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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11
Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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12
Data-Driven Approach to Modeling Biohydrogen Production from Biodiesel Production Waste: Effect of Activation Functions on Model Configurations
Published 2022“…The gradient descent optimization algorithm was observed to help improve the modelâ��s performance. …”
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13
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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14
Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh
Published 2020“…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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15
Smart phone sensor data: Comparative analysis of various classification methods for task of human activity recognition
Published 2018“…Our work has chosen sensor data of six activities such as standing, walking, laying from pre-recorded dataset gathered via smartphone to evaluate the performance of various supervised machine learning algorithms. …”
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Proceedings -
16
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Two publicly activity datasets are used; Wireless Sensor Data Mining (WISDM) and Physical Activity Monitoring for Aging People (PAMAP2). …”
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17
The effect of pre-processing techniques and optimal parameters on BPNN for data classification
Published 2015“…The architecture of artificial neural network (ANN) laid the foundation as a powerful technique in handling problems such as pattern recognition and data analysis. It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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18
Time series predictive analysis based on hybridization of meta-heuristic algorithms
Published 2018“…The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). …”
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19
Stock indicator scanner customization tool using deep reinforcement learning
Published 2022“…Other than that, many current stock indicator scanners only allow user to specify some simple conditions to scan the stocks and do not harness the advancement of machine learning. This project will deliver a web application with dynamic stock prediction model based on deep reinforcement learning or more particularly, Deep Q-Network (DQN) algorithm which enable input customization. …”
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Final Year Project / Dissertation / Thesis -
20
Analysis of online CSR message authenticity on consumer purchase intention in social media on Internet platform via PSO-1DCNN algorithm
Published 2024“…Secondly, this work designs optimization measures from inertia weight and learning factor to build an improved particle swarm optimization algorithm (IPSO). …”
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