Improving Initial Aerofoil Geometry Using Aerofoil Particle Swarm Optimisation

Müller, Jan

doi:10.13164/mendel.2022.1.063

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…Although there has been an explosion of "novel" evolutionary methods that draw on these principles [38][39][40], many of which were found to hide their lack of novelty behind a flawed experimental analysis [41][42][43][44] or a metaphor-rich jargon [45,46], these techniques are still among the most-utilized methods for diverse and complex applications, where the use of standard optimization methods is either found to be inadequate or overly computationally demanding [47,48]. Among these applications are for instance the design of mechanical components [49], quantum operators [50] or airfoil geometry [51], landslide displacement prediction [52], inverse kinematics control of a robot [53], or barrier option pricing in economics [54].…”

Section: Evolutionary Algorithmsmentioning

confidence: 99%

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Juříček,

Parák,

Kůdela

2023

Computation

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The significance of robot manipulators in engineering applications and scientific research has increased substantially in recent years. The utilization of robot manipulators to save labor and increase production accuracy is becoming a common practice in industry. Evolutionary computation (EC) techniques are optimization methods that have found their use in diverse engineering fields. This state-of-the-art review focuses on recent developments and progress in their applications for industrial robotics, especially for path planning problems that need to satisfy various constraints that are implied by both the geometry of the robot and its surroundings. We discuss the most-used EC method and the modifications that suit this particular purpose, as well as the different simulation environments that are used for their development. Lastly, we outline the possible research gaps and the expected directions future research in this area will entail.

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Section: Evolutionary Algorithmsmentioning

confidence: 99%

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Juříček,

Parák,

Kůdela

2023

Computation

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“…Synthetic minority sampling technique (SMOTE) and particle swarm optimization (PSO) are combined in the suggested classification algorithms in [29], which also incorporate many well-known classifier techniques, including logistic regression, decision tree model C5 (C5), and 1-nearest neighbor. In order to address the randomly occurring problem in a cloud computing context and improve Initial Aerofoil Geometry, the authors in [19,18] reviewed the available modified PSO scheduling methods. The comparison demonstrates that the new algorithm successfully improves upon the original PSO.…”

Section: Introductionmentioning

confidence: 99%

A Study on Heuristic Algorithms Combined With LR on a DNN-Based IDS Model to Detect IoT Attacks

Thuy¹,

Thuan

Duc

et al. 2023

mendel

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Current security challenges are made more difficult by the complexity and difficulty of spotting cyberattacks due to the Internet of Things explosive growth in connected devices and apps. Therefore, various sophisticated attack detection techniques have been created to address these issues in recent years. Due to their effectiveness and scalability, machine learning-based intrusion detection systems (IDSs) have increased. However, several factors, such as the characteristics of the training dataset and the training model, affect how well these AI-based systems identify attacks. In particular, the heuristic algorithms (GA, PSO, CSO, FA) optimized by the logistic regression (LR) approach employ it to pick critical features of a dataset and deal with data imbalance problems. This study offers an intrusion detection system (IDS) based on a deep neural network and heuristic algorithms combined with LR to boost the accuracy of attack detections. Our proposed model has a high attack detection rate of up to 99% when testing on the IoT-23 dataset.

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“…Among them are classical techniques such as the genetic algorithm (GA), the evolutionary strategy (ES), differential evolution (DE), or particle swarm optimization (PSO). Many of these methods found their use in diverse and complex applications, where the utilization of exact optimization algorithms was either found to be inadequate or computationally too expensive [9], such as the design of mechanical components [10] and quantum operators [11], feature selection [12,13], landslide displacement prediction [14], airfoil geometry design [15], or barrier option pricing in economics [16]. Another class of methods that is popular for such complex optimization problems is the class of the deterministic DIRECT (which is an acronym of DIviding RECTangles) algorithms [17].…”

Section: Introductionmentioning

confidence: 99%

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

Kudela

2023

Computers

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This paper presents a new chance-constrained optimization (CCO) formulation for the bulk carrier conceptual design. The CCO problem is modeled through the scenario design approach. We conducted extensive numerical experiments comparing the convergence of both canonical and state-of-the-art metaheuristic algorithms on the original and CCO formulations and showed that the CCO formulation is substantially more difficult to solve. The two best-performing methods were both found to be differential evolution-based algorithms. We then provide an analysis of the resulting solutions in terms of the dependence of the distribution functions of the unit transportation costs and annual cargo capacity of the ship design on the probability of violating the chance constraints.

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Improving Initial Aerofoil Geometry Using Aerofoil Particle Swarm Optimisation

Cited by 4 publications

References 8 publications

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

Evolutionary Computation Techniques for Path Planning Problems in Industrial Robotics: A State-of-the-Art Review

A Study on Heuristic Algorithms Combined With LR on a DNN-Based IDS Model to Detect IoT Attacks

Chance-Constrained Optimization Formulation for Ship Conceptual Design: A Comparison of Metaheuristic Algorithms

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