Search Results - (( parameter detection method algorithm ) OR ( risk optimization method algorithm ))
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Heart disease prediction using artificial neural network with ADAM optimization and harmony search algorithm
Published 2025“…In summary, this study advances the field by delivering an effective, optimized predictive algorithm for early heart disease detection, thereby offering valuable insights that could enhance healthcare outcomes, support proactive cardiovascular risk management, and pave the way for future innovations in personalized medicine…”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol
Published 2023“…To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…In this task, two neural network algorithms, Recurrent Neural Networks (RNN) and Multi-Layer Perceptron Neural Networks (MLP-NN) were used and the hyper-parameters of the network architecture was optimized based on a systematic grid search. …”
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Early detection of dengue disease using extreme learning machine
Published 2018“…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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CT reconstruction algorithm and low contrast detectability of phantom study: a systematic review and meta-analysis
Published 2022“…Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. …”
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Groundwater quality assessment and optimization of monitored wells using multivariate geostatistical techniques in Amol-Babol Plain, Iran
Published 2015“…DRASTIC model was applied as a vulnerability assessment method based on the physical environmental aquifer parameters for assessing potential risk zone of aquifer to contamination, which showed more than 88% of the total area was classified as low to moderate risk to pollutant. …”
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Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost
Published 2024“…PSO-EBGWO is used to optimize the parameters of the CatBoost model. In this method, the Gray Wolf optimized algorithm (EBGWO) is further optimized by particle swarm optimization (PSO), and when combined with it, the convergence performance of the model is improved, the parameters of the model are reduced, and the model is simplified. …”
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Multi-Objective Portfolio Optimization Strategy using the SPEA-II Algorithm
Published 2025“…The study highlights that the SPEA-II algorithm can serve as an effective and efficient method for stock portfolio selection and optimization, helping investors to identify portfolios with lower risk and higher return…”
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Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The simulation results indicate that the proposed method is suitable to detect a single outlier. As for the multiple outliers, a clustering algorithm is considered and a dendogram to visualise the clustering algorithm is used. …”
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Application of weighted average on modal parameters for damage detection algorithms: Case study on steel beam
Published 2011“…This study verifies the use of the proposed weighting method by Fayyadh and Abdul Razak (2011a) for damage detection algorithms applied on cracked steel beam. …”
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Weighting method for modal parameter based damage detection algorithms
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…This creates the jamming detection and classification parameters. The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
Published 2014“…This study focuses on using GSA method, a new computational intelligence algorithm. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. …”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…While conventional numerical methods can be applied, they often struggle with inefficiency and fail to deliver optimal results. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The NTLBO was proposed in this paper as an FSS mechanism; its algorithm-specific, parameter-less concept (which requires no parameter tuning during an optimization) was explored. …”
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Optimizing Visual Sensors Placement with Risk Maps Using Dynamic Programming
Published 2022“…This article explores the efficiency of the visual sensor placement based on a combination of two methods namely, a deterministic risk estimation for the risk assessment and a dynamic programming for optimizing the placement of surveillance cameras. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…The existence of outliers in a circular regression model can lead to many errors, for example in inferences and parameter estimations. Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM
Published 2025“…EMA was applied for hyperparameter optimization, demonstrating improved convergence and generalization over conventional methods. …”
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