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Predictive models in software engineering: Challenges and opportunities
Predictive models are one of the most important techniques that are widely applied in many
areas of software engineering. There have been a large number of primary studies that …
areas of software engineering. There have been a large number of primary studies that …
Metaheuristic algorithms in optimizing deep neural network model for software effort estimation
Effort estimation is the most critical activity for the success of overall solution delivery in
software engineering projects. In this context, the paper's main contributions to the literature …
software engineering projects. In this context, the paper's main contributions to the literature …
Ensemble effort estimation with metaheuristic hyperparameters and weight optimization for achieving accuracy
Software development effort estimation (SDEE) is recognized as vital activity for effective
project management since under or over estimating can lead to unsuccessful utilization of …
project management since under or over estimating can lead to unsuccessful utilization of …
Genetic algorithm based probabilistic model for agile project success in global software development
Software development organizations implement agile methods in global software
development (GSD) to leverage benefits in terms of low development cost, continuous …
development (GSD) to leverage benefits in terms of low development cost, continuous …
Multi-label classification to predict antibiotic resistance from raw clinical MALDI-TOF mass spectrometry data
Antimicrobial resistance (AMR) poses a significant global health challenge, necessitating
advanced predictive models to support clinical decision-making. In this study, we explore …
advanced predictive models to support clinical decision-making. In this study, we explore …
[HTML][HTML] Genetic model-based success probability prediction of quantum software development projects
Context Quantum computing (QC) holds the potential to revolutionize computing by solving
complex problems exponentially faster than classical computers, transforming fields such as …
complex problems exponentially faster than classical computers, transforming fields such as …
Optimizing Deep Learning Model for Software Cost Estimation Using Hybrid Meta‐Heuristic Algorithmic Approach
Effective software cost estimation significantly contributes to decision‐making. The rising
trend of using nature‐inspired meta‐heuristic algorithms has been seen in software cost …
trend of using nature‐inspired meta‐heuristic algorithms has been seen in software cost …
Risk assessment in new software development projects at the front end: a fuzzy logic approach
MY Hsieh, YC Hsu, CT Lin - Journal of Ambient Intelligence and …, 2018 - Springer
New software development (NSD) has inherent complexity, uncertainty, and risk. Risk
analysis and mitigation is perhaps the most critical activity in an NSD project, yet such risk …
analysis and mitigation is perhaps the most critical activity in an NSD project, yet such risk …
6G secure quantum communication: a success probability prediction model
The emergence of 6G networks initiates significant transformations in the communication
technology landscape. Yet, the melding of quantum computing (QC) with 6G networks …
technology landscape. Yet, the melding of quantum computing (QC) with 6G networks …
Systems thinking in software projects-an artificial neural network approach
The authors discuss why the current conceptual base of project management research and
practice continues to attract criticism since it does not adequately address the complexity …
practice continues to attract criticism since it does not adequately address the complexity …