Search Results - (( using optimization method algorithm ) OR ( knowledge prediction using algorithm ))
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1
An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…Moreover, Butterfly Optimization Algorithm and Harmony Search Algorithm were combined as optimization method led to a new method named BOAHS. …”
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Thesis -
2
Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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3
Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Pr...
Published 2024“…A coati optimization algorithm is introduced to select input scenarios. …”
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4
Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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5
Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm
Published 2024“…The experimental results demonstrate that the DSA optimized RFR algorithm achieves RMSE of 0.382% in the HPPC test using LiNMC battery. …”
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Optimized feature construction methods for data summarizations of relational data
Published 2014“…Many approaches have been developed to discover knowledge (i.e. useful information) from data stored in multiple tables in a relational database. …”
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7
Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm
Published 2010“…In particular, GA is being extensively used in the field of optimization. This paper discusses the utilization of GA in estimating the coefficients and exponents in developing the Nusselt Number correlation in two different heat exchanger geometries, with the aim to reduce the error incurred in predicting heat transfer coefficients and heat transfer rates. …”
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Final Year Project -
8
Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…Experimentally observed responses were used to train, map and optimize the network algorithms before the best architecture was selected. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…In this regards, a new method of Pico-satellite attitude control using Mamdani Fuzzy Logic Principles is introduced. …”
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10
Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction
Published 2024“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…This study will use the Extreme Learning Machine (ELM) method to classify the dengue by using the clinical data so that first aid can be given which can decrease some death risk. …”
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12
Predicting next page access by Markov models and association rules on web log data
Published 2006“…This algorithm has been used to cluster Web site with similar transition behaviors and compares the transition matrix to an optimal size for efficient used to further improve the efficiency of prediction. …”
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Classification with degree of importance of attributes for stock market data mining
Published 2004“…The experimental results show that predictive FDT algorithm can generate a relatively optimal tree without much computation effort (comprehensibility), and WFPRs have a better predictive accuracy of stock market time series data. …”
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15
Accurate and reliable diagnosis and classification using probabilistic ensemble simplified fuzzy ARTMAP
Published 2005“…For the medical diagnosis and classification problems, PESFAM achieves 100 percent in accuracy, specificity, and sensitivity based on the 10-fold crossvalidation and these results are superior to those from other classification algorithms. In addition, a posteri probability of the predicted class can be used to measure the prediction reliability of PESFAM. …”
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Solubility enhancement of decitabine as anticancer drug via green chemistry solvent: Novel computational prediction and optimization
Published 2022“…ADA-LR was selected as the primary model according to numerical and visual analysis. Finally, the optimal values are (P = 400 bar, T = 3.38 K 102, Y = 1.064 10ˉ³ mol fraction) using this model.…”
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Modelling knowledge transfer of nursing students during clinical placement / Nor Azairiah Fatimah Othman
Published 2017“…An efficient optimization method using PSO for synchronizing torque coefficients Ks and damping torque coefficients Kd to solve angle stability problems was developed and used to identify the angle stability condition on single and multi machine system. …”
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Book Section -
18
Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor
Published 2017“…The backpropagation neural network model with Lavenberg Marquardt learning algorithm was developed using 1476 samples real process dataset obtained from a fermentation process in a 200L bioreactor. …”
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Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…Step 3 automatically evolves the best-fitting parameters for the highly personalized model at each center using an adapted genetic algorithm. Ultimately, this typical "FL training + local adaptation" PFL method can enhance model predictive accuracy by automatically generating a highly personalized model for each ICU center, guided by the FL sharing model. …”
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