☆ 4.6 Article

Parallel Metaheuristic Algorithms for Solving Imbalanced Data Classification Problems

IEEE ACCESS (2023)

Related references

Note: Only part of the references are listed.

Article Computer Science, Artificial Intelligence

The monarch butterfly optimization algorithm for solving feature selection problems

Mohammed Alweshah et al.

Summary: This study combined the latest Monarch Butterfly Optimization algorithm with a wrapper feature selection method using k-nearest neighbor classifier, and conducted experiments on 18 benchmark datasets. The results showed that the MBO algorithm was superior to other algorithms in terms of high classification accuracy rate and reduced selection size.

NEURAL COMPUTING & APPLICATIONS (2022)

Add to Collection

Article Geosciences, Multidisciplinary

A probabilistic neural network (PNN) based framework for lithology classification using seismic attributes

Soumi Chaki et al.

Summary: This paper proposes a framework based on Probabilistic Neural Network (PNN) for lithology classification using seismic attributes. The framework is compared with existing supervised classifiers in terms of performance measures such as classification accuracy, sensitivity, and specificity. The study also investigates the selection of appropriate parameters for the classifiers and the importance of individual seismic predictors. The framework is shown to be helpful in estimating the probability of hydrocarbon presence in a large study area.

JOURNAL OF APPLIED GEOPHYSICS (2022)

Add to Collection

Article Chemistry, Analytical

American Sign Language Words Recognition of Skeletal Videos Using Processed Video Driven Multi-Stacked Deep LSTM

Sunusi Bala Abdullahi et al.

Summary: This paper proposes a method to enhance the feature vector of dynamic sign words using knowledge of hand dynamics, and classify them based on motion patterns. It is found that some double-hand dynamic sign words have ambiguous or similar features in hand motion trajectory, leading to classification errors. Therefore, the similar/ambiguous hand motion trajectory is determined based on the approximation of a probability density function, and the extracted features are enhanced using maximal information correlation. The proposed method outperforms conventional methods on challenging ASL, SHREC, and LMDHG datasets.

SENSORS (2022)

Add to Collection

Article Engineering, Civil

Guided Water Strider Algorithm for Structural Damage Detection Using Incomplete Modal Data

Ali Kaveh et al.

Summary: In this paper, a guided structural damage detection approach using the water strider algorithm (WSA) is proposed to detect multiple damage cases in structures by utilizing modal strain energy to localize damage locations and guide the optimization algorithm. Through four numerical examples with both noisy and noise-free scenarios, the results demonstrate the applicability and accuracy of WSA in structural damage detection compared to other algorithms.

IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING (2022)

Add to Collection

Article Social Issues

Nonprofit Role Classification Using Mission Descriptions and Supervised Machine Learning

Megan LePere-Schloop

Summary: Scholars have studied nonprofit roles using both quantitative and qualitative approaches. Machine learning can now be used to classify a large set of mission descriptions, and this approach may yield more fruitful results in future research.

NONPROFIT AND VOLUNTARY SECTOR QUARTERLY (2022)

Add to Collection

Review Management

Metaheuristics In the Large

Jerry Swan et al.

Summary: Metaheuristics have been a great success story in optimization research after decades of sustained improvement. To avoid fragmentation and lack of reproducibility, stronger scientific and computational infrastructure is needed. The Metaheuristics In the Large project aims to provide extensible algorithm templates, white box problem descriptions, and remotely accessible frameworks to enhance reproducibility and accelerate progress in the field. Through common protocols, the field can explore the design space of metaheuristics more efficiently.

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH (2022)

Add to Collection

Article Computer Science, Information Systems

African buffalo algorithm: Training the probabilistic neural network to solve classification problems

Mohammed Alweshah et al.

Summary: Classification is a method to categorize and make decisions on data. Researchers use hybridization of neural networks with other algorithms to improve accuracy. In this paper, the African buffalo optimization (ABO) algorithm is used to adjust the weights of the probabilistic neural network (PNN) for better performance in classification problems.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2022)

Add to Collection

Article Biology

BERT-Promoter: An improved sequence-based predictor of DNA promoter using BERT pre-trained model and SHAP feature selection

Nguyen Quoc Khanh Le et al.

Summary: In this study, a novel architecture combining Transformer natural language processing and explainable machine learning was proposed to predict DNA promoters and their activities. Experimental results showed that our predictor outperformed previous predictors in terms of accuracy.

COMPUTATIONAL BIOLOGY AND CHEMISTRY (2022)

Add to Collection

Article Computer Science, Information Systems

Neuro-evolutionary models for imbalanced classification problems

Israa Al-Badarneh et al.

Summary: This paper introduces three stochastic and metaheuristic algorithms to train MLP neural network for solving the problem of imbalanced classifications. The algorithms are evaluated using accuracy, F-score, and G-mean, and the results show that F-score and G-mean are more advantageous when the datasets are imbalanced.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2022)

Add to Collection

Article Chemistry, Medicinal

Identifying SNARE Proteins Using an Alignment-Free Method Based on Multiscan Convolutional Neural Network and PSSM Profiles

Nguyen Quoc Khanh Le et al.

Summary: This paper proposes a novel model based on a multiscan convolutional neural network and position-specific scoring matrix for predicting and recognizing SNARE proteins. Experimental results demonstrate that the model performs well in SNARE classification and recognition tasks.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2022)

Add to Collection

Article Biochemical Research Methods

DNA Privacy: Analyzing Malicious DNA Sequences Using Deep Neural Networks

Ho Bae et al.

Summary: Recent advances in next-generation sequencing technologies have allowed the successful insertion of video information into DNA. A sequence-learning-based malicious DNA sequence analysis method has been proposed to address the limitations of conventional steganalysis algorithms in detecting DNA steganography.

IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS (2022)

Add to Collection

Article Computer Science, Artificial Intelligence

Comparative analysis of image classification algorithms based on traditional machine learning and deep learning

Pin Wang et al.

Summary: This paper compares and analyzes traditional machine learning and deep learning image classification algorithms, finding that traditional machine learning performs better on small sample datasets, while deep learning has higher recognition accuracy on large sample datasets.

PATTERN RECOGNITION LETTERS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

A hybrid mine blast algorithm for feature selection problems

Mohammed Alweshah et al.

Summary: Feature selection is a crucial preprocessing step for data mining techniques, improving prediction process speed and accuracy, and providing a better understanding of stored data. In this study, two methods were proposed to enhance the feature selection process, with the MBA-SA approach showing good performance across 18 benchmark datasets.

SOFT COMPUTING (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Solving feature selection problems by combining mutation and crossover operations with the monarch butterfly optimization algorithm

Mohammed Alweshah

Summary: This study introduces an improved FS wrapper method using the MBO algorithm to enhance KSN classification. Two modified algorithms (MBOICO and MBOLF) are tested on 25 datasets, with MBOICO showing the best performance in terms of accuracy rate and selection size reduction.

APPLIED INTELLIGENCE (2021)

Add to Collection

Article Engineering, Biomedical

Machine learning techniques for mitoses classification

Shima Nofallah et al.

Summary: This study evaluated the performance of two state-of-the-art CNNs, ESPNet and DenseNet, for mitosis classification in skin biopsies. DenseNet showed higher sensitivity and specificity compared to ESPNet on the primary melanoma dataset, and both models performed well on the MITOS dataset. DenseNet outperformed other architectures in terms of F-score and recall on the MITOS dataset, despite having longer inference times.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2021)

Add to Collection

Article Automation & Control Systems

Optimization of Type-2 Fuzzy Logic Controller Design Using the GSO and FA Algorithms

Emer Bernal et al.

Summary: This study presents a comparative analysis between the firefly algorithm and galactic swarm optimization method in optimizing a fuzzy controller for an autonomous mobile robot. It finds the best method for generating optimal values for the membership function vector, aiming to improve controller performance and trajectory accuracy. The results show that GSO outperforms FA in designing interval type-2 fuzzy controllers.

INTERNATIONAL JOURNAL OF FUZZY SYSTEMS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Big data analytics and machine learning: A retrospective overview and bibliometric analysis

Justin Zuopeng Zhang et al.

Summary: The study analyzed the contributions of major authors, universities/organizations, and countries in the information systems field through bibliometric analysis. The publications were grouped into five clusters, with Cluster 1 consistently dominating the landscape. Other clusters covered areas such as IoT, security, cloud computing, social media analytics, and classification predictive research.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Add to Collection

Review Biochemical Research Methods

Parallel computing for genome sequence processing

You Zou et al.

Summary: The rapid increase of genome data from gene sequencing technologies presents a massive challenge to data processing. To address this, researchers have proposed methods in big data storage, efficient algorithm design, and parallel computing. This review investigates popular parallel programming technologies for genome sequence processing, discussing models, applications, and limitations.

BRIEFINGS IN BIOINFORMATICS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

A Neighborhood Undersampling Stacked Ensemble (NUS-SE) in imbalanced classification

Zian Seng et al.

Summary: The proposed NUS-SE method integrates undersampling into stacked ensemble to improve classification performance on imbalanced datasets. It consists of a base undersampling-based stacked ensemble framework and an undersampling technique component. The NUS-SE outperforms non-resampling based stacked ensemble methods in terms of classification performance.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Optimization of SMOTE for imbalanced data based on AdaRBFNN and hybrid metaheuristics

Zicheng Wang et al.

Summary: This study proposes a hyperparameter optimization algorithm to address the issue of imbalanced dataset classification. By iterating to find suitable hyperparameters, the algorithm constructs a balanced and high-quality dataset, training a model with outstanding performance and strong generalization ability.

INTELLIGENT DATA ANALYSIS (2021)

Add to Collection

Article Automation & Control Systems

Using two metaheuristic algorithms for scheduling parallel machines with sequence dependent set-up times in job shop industries

Ghorbanali Mohammadi et al.

Summary: Scheduling problem in production planning is explored with the use of metaheuristic algorithms such as Ant colony optimisation and Harmony Search algorithm. Performance is analyzed and efficient algorithms are investigated by comparing them with other algorithms.

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

A conditional variational autoencoder based self-transferred algorithm for imbalanced classification

Yudi Zhao et al.

Summary: In this paper, a conditional variational autoencoder-based self-transferred algorithm is proposed to address highly imbalanced classification problems. The method utilizes information from both majority and minority classes for domain knowledge transfer, while conducting distribution learning, image generation, and dataset rebalancing in a unified framework. Experimental results demonstrate the effectiveness of the approach in both imbalanced datasets and real-world industrial applications.

KNOWLEDGE-BASED SYSTEMS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

Salp Swarm Optimizer for Modeling Software Reliability Prediction Problems

Sofian Kassaymeh et al.

Summary: Software effort prediction and software test prediction problems are tackled by integrating SSA with BPNN in this paper to improve prediction accuracy. The proposed SSA-BPNN method is tested on twelve SEP datasets and two STP datasets, outperforming other state-of-the-art methods for most performance measures.

NEURAL PROCESSING LETTERS (2021)

Add to Collection

Article Computer Science, Artificial Intelligence

An efficient chaotic salp swarm optimization approach based on ensemble algorithm for class imbalance problems

Rekha Gillala et al.

Summary: This paper introduces an AdaBoost algorithm with chaotic salp swarm optimization, which can effectively address class imbalance issues. Experiments demonstrate the technique's ability to find optimal features and maximize the performance of AdaBoost.

SOFT COMPUTING (2021)

Add to Collection

Article Engineering, Chemical

Partitional Clustering-Hybridized Neuro-Fuzzy Classification Evolved through Parallel Evolutionary Computing and Applied to Energy Decomposition for Demand-Side Management in a Smart Home

Yu-Chen Hu et al.

Summary: Smart meters allow for transmission of energy consumption data and enable consumer-centric use cases, but are unable to decompose energy consumption data into appliance-level data. The AI model introduced in the research can effectively perform energy decomposition in residential demand-side management.

PROCESSES (2021)

Add to Collection

Proceedings Paper Computer Science, Artificial Intelligence

A Feature Selection Method Based on Hybrid Natural Inspired Algorithms

Xiaoyu Xia et al.

Summary: Data mining is a rapidly growing research field in the information industry, and feature selection is a critical preprocessing step that affects the performance of data mining. The proposed parallel model THDWL improves classification accuracy and convergence speed effectively.

PROCEEDINGS OF THE 11TH IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT DATA ACQUISITION AND ADVANCED COMPUTING SYSTEMS: TECHNOLOGY AND APPLICATIONS (IDAACS'2021), VOL 2 (2021)

Add to Collection

Proceedings Paper Computer Science, Information Systems

OPNN: Optimized Probabilistic Neural Network based Automatic Detection of Maize Plant Disease Detection

Eisha Akanksha et al.

Summary: Agriculture is a crucial sector of the Indian economy, with maize being the most important food crop. However, plant diseases pose a major challenge in agricultural production. To address this issue, an efficient automated maize plant diagnosis method has been developed, involving four stages for processing.

PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT 2021) (2021)

Add to Collection

Article Computer Science, Interdisciplinary Applications

Evaluation and comparison of the advanced metaheuristic and conventional machine learning methods for the prediction of landslide occurrence

Chao Yuan et al.

ENGINEERING WITH COMPUTERS (2020)

Add to Collection

Article Computer Science, Information Systems

Class-specific attribute value weighting for Naive Bayes

Huan Zhang et al.

INFORMATION SCIENCES (2020)

Add to Collection

Article Chemistry, Analytical

A Metaheuristic Optimization Approach for Parameter Estimation in Arrhythmia Classification from Unbalanced Data

Juan Carlos Carrillo-Alarcon et al.

SENSORS (2020)

Add to Collection

Article Engineering, Civil

Water strider algorithm: A new metaheuristic and applications

A. Kaveh et al.

STRUCTURES (2020)

Add to Collection

Article Engineering, Civil

Dynamic Water Strider Algorithm for Optimal Design of Skeletal Structures

Ali Kaveh et al.

PERIODICA POLYTECHNICA-CIVIL ENGINEERING (2020)

Add to Collection

Article Engineering, Civil

An Improved Water Strider Algorithm for Optimal Design of Skeletal Structures

Ali Kaveh et al.

PERIODICA POLYTECHNICA-CIVIL ENGINEERING (2020)

Add to Collection

Article Multidisciplinary Sciences

Understanding the role of individual units in a deep neural network

David Bau et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2020)

Add to Collection

Article Oncology

PNN and KCNQ1OT1 Can Predict the Efficacy of Adjuvant Fluoropyrimidine-Based Chemotherapy in Colorectal Cancer Patients

Andrea Lapucci et al.

ONCOLOGY RESEARCH (2020)

Add to Collection

Article Computer Science, Artificial Intelligence

Evolving Unsupervised Deep Neural Networks for Learning Meaningful Representations

Yanan Sun et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2019)

Add to Collection

Article Computer Science, Artificial Intelligence

A bi-objective hybrid algorithm for the classification of imbalanced noisy and borderline data sets

Sana Saeed et al.

PATTERN ANALYSIS AND APPLICATIONS (2019)

Add to Collection

Article Computer Science, Artificial Intelligence

FF-SMOTE: A Metaheuristic Approach to Combat Class Imbalance in Binary Classification

Prabhjot Kaur et al.

APPLIED ARTIFICIAL INTELLIGENCE (2019)

Add to Collection

Article Computer Science, Artificial Intelligence

Ensemble classification for imbalanced data based on feature space partitioning and hybrid metaheuristics

Pedro Lopez-Garcia et al.

APPLIED INTELLIGENCE (2019)

Add to Collection

Article Mathematical & Computational Biology

Optimization of Neural Network Using Improved Bat Algorithm for Data Classification

Waqas Haider Bangyal et al.

JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS (2019)

Add to Collection

Article Computer Science, Interdisciplinary Applications

The role of demographics in online learning; A decision tree based approach

Saman Rizvi et al.

COMPUTERS & EDUCATION (2019)

Add to Collection

Article Computer Science, Interdisciplinary Applications

A survey on new generation metaheuristic algorithms

Tansel Dokeroglu et al.

COMPUTERS & INDUSTRIAL ENGINEERING (2019)

Add to Collection

Article Engineering, Electrical & Electronic

Evaluation of PNN pattern-layer activation function approximations in different training setups

Nikolay T. Dukov et al.

INTERNATIONAL JOURNAL OF SPEECH TECHNOLOGY (2019)

Add to Collection

Article Computer Science, Information Systems

A Novel Hybrid Model for Stock Price Forecasting Based on Metaheuristics and Support Vector Machine

Mojtaba Sedighi et al.

DATA (2019)

Add to Collection

Article Computer Science, Hardware & Architecture

METADOCK: A parallel metaheuristic schema for virtual screening methods

Baldomero Imbernon et al.

INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS (2018)

Add to Collection

Article Forestry

Characterizing the dynamics of cone production for longleaf pine forests in the southeastern United States

Xiongwen Chen et al.

FOREST ECOLOGY AND MANAGEMENT (2018)

Add to Collection

Article Computer Science, Artificial Intelligence

Adaptive multi-objective swarm fusion for imbalanced data classification

Jinyan li et al.

INFORMATION FUSION (2018)

Add to Collection

Article Computer Science, Information Systems

Big Data Analytics, Machine Learning, and Artificial Intelligence in Next-Generation Wireless Networks

Mirza Golam Kibria et al.

IEEE ACCESS (2018)

Add to Collection

Article Computer Science, Artificial Intelligence

Enterprise credit risk evaluation based on neural network algorithm

Xiaobing Huang et al.

COGNITIVE SYSTEMS RESEARCH (2018)

Add to Collection

Article Computer Science, Software Engineering

A comparative study of the class imbalance problem in Twitter spam detection

Chaoliang Li et al.

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2018)

Add to Collection

Article Computer Science, Information Systems

Machine Learning With Big Data: Challenges and Approaches

Alexandra L'Heureux et al.

IEEE ACCESS (2017)

Add to Collection

Article Computer Science, Information Systems

Addressing the class imbalance problem in Twitter spam detection using ensemble learning

Shigang Liu et al.

COMPUTERS & SECURITY (2017)

Add to Collection

Review Computer Science, Artificial Intelligence

Learning from imbalanced data: open challenges and future directions

Bartosz Krawczyk

PROGRESS IN ARTIFICIAL INTELLIGENCE (2016)

Add to Collection

Article Automation & Control Systems

A Taguchi-Based Heterogeneous Parallel Metaheuristic ACO-PSO and Its FPGA Realization to Optimal Polar-Space Locomotion Control of Four-Wheeled Redundant Mobile Robots

Hsu-Chih Huang

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2015)

Add to Collection

Article Environmental Sciences

Classification of remote sensed data using Artificial Bee Colony algorithm

J. Jayanth et al.

EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES (2015)

Add to Collection

Article Computer Science, Artificial Intelligence

Weighted extreme learning machine for imbalance learning

Weiwei Zong et al.

NEUROCOMPUTING (2013)

Add to Collection

Article Computer Science, Artificial Intelligence

KEEL: a software tool to assess evolutionary algorithms for data mining problems

J. Alcala-Fdez et al.

SOFT COMPUTING (2009)

Add to Collection

Article Computer Science, Software Engineering

Classifying Data Streams with Skewed Class Distributions and Concept Drifts

Jing Gao et al.

IEEE INTERNET COMPUTING (2008)

Add to Collection

Article Mathematics, Applied

Efficient optimization of support vector machine learning parameters for unbalanced datasets

Tatjana Eitrich et al.

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS (2006)

Add to Collection

© Peeref 2019-2024. All rights reserved.