ComputationSoft ComputingOptimisation algorithmsParticle2022MetaheuristicsParallelNeuralAdaptiveComputationalTomographyNSGA-IIDifferential EvolutionConstraintEdge detectionDescribesGenetic ProgrammingBiologicallyFuzzy systemsMathematicalDetectionHigh PerformanEfficiencySearchNature inspiredExperimentalEnvironmentsResearchSystemsDesignCellularProblemsApplicationsDataMachineApproachesMethodsNonlinear
Computation12
- The baseline is that Perl is a language as good as any to do Evolutionary Computation, and probably better than many others. (blogalia.com)
- Relevant research should apply solution approaches that incorporate genetic programming and metaheuristics (evolutionary computation, local search methods) as well as soft computing techniques (neural networks, fuzzy systems). (mdpi.com)
- GECCO-99 : proceedings of the genetic and evolutionary computation conference. (napier.ac.uk)
- Evolutionary Computation (2017) 25 (3): 351-373. (mit.edu)
- In this paper, a novel algorithm is proposed to help K-means jump out of a local optimum on the basis of several ideas from evolutionary computation, through the use of random and evolutionary processes. (techscience.com)
- The Genetic and Evolutionary Computation Conference (GECCO-2000) will present the latest high-quality research results in the growing field of genetic and evolutionary computation. (colostate.edu)
- Evolutionary Computation (ECJ) , 27 (4), 577-609. (uni-muenster.de)
- Evolutionary Computation, 2004. (google.co.uk)
- Evolutionary computation is emerging as a novel engineering computational paradigm, which plays a significant role in several optimization problems. (amrita.edu)
- In this paper an eminent approach based on the paradigms of evolutionary computation for solving job shop scheduling problem is proposed. (amrita.edu)
- IEEE Transactions on Evolutionary Computation 2017 21(6): 863-877 DOI: 10.1109/TEVC.2017.2688863. (cinvestav.mx)
- Evolutionary Computation (2005) 13 (2): 213-239. (mit.edu)
Soft Computing22
- has finally been published (online first) in the Soft Computing . (blogalia.com)
- In this article, the detailed description of the algorithm 'Evolutionary published in Soft Computing' is shared. (blogalia.com)
- Recently, Genetic Programming (GP) and related soft computing methods have gained significant attention from the research community. (mdpi.com)
- Due to the wide range of applications, as well as the recent advances made in the field of genetic programming and soft computing, it is expected that this area of research will continue to attract the attention of the research community and lead to new significant advances. (mdpi.com)
- This Special Issue provides an opportunity for researchers to publish their new work in the field of genetic programming and soft computing. (mdpi.com)
- IJAISC provides a new forum for dissemination of knowledge on both theoretical and applied research on artificial intelligence and soft computing with an ultimate aim to bridge the gap between these two non-coherent disciplines of knowledge. (inderscience.com)
- IJAISC thus meets the demands of both theoretical and applied researchers in artificial intelligence and soft computing. (inderscience.com)
- IJAISC provides a vehicle to help professionals, academicians and researchers working in the field of artificial intelligence and soft computing. (inderscience.com)
- Soft Computing (2019) 23 (17): 7913. (mit.edu)
- Intelligent Automation & Soft Computing 2020 , 26 (5), 961-971. (techscience.com)
- 8 Natural Parallel (Soft) Computing. (osiander.de)
- The authors explain that soft computing is a term covering such computing methodologies which are, in some sense, tolerant of imprecision, uncertainty and partial truth. (osiander.de)
- The reviewed book is intended both for undergraduate students in soft computing disciplines as well as for engineers, practitioners, and problem solvers in many areas of application. (osiander.de)
- The main theme of the reviewed book is integration and synergistic co-operation of a few soft-computing methodologies that have their roots in neural systems. (osiander.de)
- The book Soft Computing: Integrating Evolutionary, Neural and Fuzzy Systems provides a comprehensive introduction to the area of soft computing addressing three of the main constituents of this discipline: fuzzy logic, neural computing and evolutionary computing. (osiander.de)
- Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. (osiander.de)
- Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. (osiander.de)
- Applied Soft Computing 2017 50: 48-57 DOI: 10.1016/j.asoc.2016.10.037. (cinvestav.mx)
- Soft Computing 2017 21(19): 5647-5663 DOI: 10.1007/s00500-016-2140-z. (cinvestav.mx)
- Soft Computing 2017 21(4): 861-884 DOI: 10.1007/s00500-015-1819-x. (cinvestav.mx)
- The discipline of nature-inspired optimization algorithms is a major field of computational intelligence, soft computing and optimization. (theiet.org)
- The aim of this edited book is to review the intertwining disciplines of nature-inspired computing and bio-inspired soft-computing (BISC) and their applications to real world challenges. (theiet.org)
Optimisation algorithms1
- Nature inspired machine learning and approximate reasoning techniques that include combinations of fuzzy logic systems, neural networks, evolutionary optimisation algorithms, cooperative systems. (essex.ac.uk)
Particle4
- The feature reduction step includes genetic algorithm (GA), particle swarm optimisation (PSO) and ant colony optimisation (ACO) in the performance analysis to determine the best approach. (inderscience.com)
- Here we proposed a novel algorithm that uses Particle Swarm Optimization (PSO) algorithm to determine the cluster boundaries in the output of self-organizing map (SOM). (usp.ac.fj)
- Particle Swarm Optimization (PSO) is one of the newly developed algorithms being investigated internationally. (usp.ac.fj)
- evolutionary algorithms, particle and swarm methods, and biologically motivated algorithms. (sdsmt.edu)
20222
- Martínez-Cagigal, Víctor and Santamaría-Vázquez, Eduardo and Hornero, Roberto, Brain-Computer Interface Channel Selection Optimization Using Meta-Heuristics and Evolutionary Algorithms (October 18, 2022). (ssrn.com)
- Article: Feature selection using evolutionary algorithms: a data-constrained environment case study to predict tax defaulters Journal: International Journal of Cloud Computing (IJCC) 2022 Vol.11 No.4 pp.345 - 355 Abstract: In this paper, a novel method is introduced to predict tax defaulters from the given data using an ensemble of feature reduction in the first step and feeding those features to a proposed neural network. (inderscience.com)
Metaheuristics1
- The contributors cover the interaction between metaheuristics, such as evolutionary algorithms and swarm intelligence, with complex systems. (theiet.org)
Parallel1
- Parallel and distributed computing in optimization - Cloud computing, GPGPU computing environment. (just.edu.jo)
Neural6
- Further, the Artificial Neural Network (ANN), which is one of the most successful machine learning algorithms, is used to predict the virtual machines based on the characteristics of tasks and features of the resources. (springer.com)
- Applying Linear Regression and Neural Network Meta-Models for Evolutionary Algorithm Based Simulation Optimization. (ncsu.edu)
- 4 Evolutionary Design of Artificial Neural Networks. (osiander.de)
- There are three of them exposed in this book, namely: fuzzy logic, evolutionary algorithms and artificial neural networks - all inspired by nature. (osiander.de)
- This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. (osiander.de)
- In our supply chain, neural networks are the main drivers behind the inventory management system recommending specific vehicle configurations to dealers, and evolutionary computing algorithms (in conjunction with dynamic semantic network-based expert systems) are deployed in support of resource management in assembly plants. (oreilly.com)
Adaptive2
- The adaptive operator selection (AOS) and the adaptive parameter control are widely used to enhance the search power in many multiobjective evolutionary algorithms. (hindawi.com)
- This paper proposes a novel adaptive selection strategy with bandits for the multiobjective evolutionary algorithm based on decomposition (MOEA/D), named latest stored information based adaptive selection (LSIAS). (hindawi.com)
Computational3
- Thus, bio-inspired computing is a multi-disciplinary field devoted to studying complex problems using computational methods modeled after design principles encountered in nature. (wikicfp.com)
- Over the course of my career, I have worked in both industrial and academia developing and applying nature inspired Computational Intelligence (CI) approaches for human centred systems related to various real-world domains such as smart environments, elderly care, energy optimization, industrial automation, information analysis, decision-making simulation, control systems and affective computing. (essex.ac.uk)
- Nature-inspired computing is oriented towards the application of outstanding information-processing aptitudes of the natural realm to the computational domain. (theiet.org)
Tomography1
- Computed tomography (CT) scans carry a risk of teratogenesis and childhood hematologic malignancies but may be used judiciously with minimized radiation protocols (2-5 rads). (medscape.com)
NSGA-II1
- In order to control the energy consumption efficaciously, the Dynamic Voltage Frequency Scaling system is incorporated in the optimization procedure and a set of non-domination solutions are obtained using Non-dominated Sorting Genetic Algorithm (NSGA-II). (springer.com)
Differential Evolution2
- Is Differential Evolution a genetic algorithm? (stackexchange.com)
- The Differential Evolution (DE) algorithm, which is one of the popular optimization algorithms in the category of Evolutionary Algorithms (EAs), is known for its simplicity and wide applicability. (amrita.edu)
Constraint1
- I developed a variation of EA - Intelligent constraint handling evolutionary algorithm (ICHEA) that has been demonstrated to be a versatile constraints-guided EA for all forms of constrained problems on several benchmark problems. (usp.ac.fj)
Edge detection2
- This paper presents an experiment which evaluate the performances of three different evolutionary algorithms on edge detection. (actapress.com)
- Currently, I am working on image edge detection using evolutionary algorithms. (usp.ac.fj)
Describes1
- The population model of an evolutionary algorithm (EA) describes the structural properties of its population to which its members are subject. (wikipedia.org)
Genetic Programming1
- Conference operated by the International Society for Genetic Algorithms, Inc., a Massachusetts not-for-profit corporation and Genetic Programming, Inc., a California Corporation. (colostate.edu)
Biologically2
- The 13th World Congress on Nature and Biologically Inspired Computing (NaBIC 2021) brings together international researchers, developers, practitioners, and users. (wikicfp.com)
- NaBIC 2021 invites authors to submit their original and unpublished work that demonstrates current research in all areas of Nature and Biologically Inspired Computing, as well as proposals for workshops, industrial presentations, demonstrations, and tutorials. (wikicfp.com)
Fuzzy systems1
- 5 Evolutionary Design of Fuzzy Systems. (osiander.de)
Mathematical1
- Even better, it possesses capabilities in "reverse optimization using various mathematical algorithms, fuzzy logic, genetic algorithms [and] evolutionary computing. (theregister.com)
Detection2
- Recently, there has been considerable research on active fault detection and model identification algorithms for linear systems. (ncsu.edu)
- These algorithms compute an auxiliary input signal which guarantees fault detection, assuming a bounded noise. (ncsu.edu)
High Performan3
- This session aims at examining different solutions to complex problems using nature inspired approaches, and their interplay with cutting-edge technology in High Performance Computing. (wikicfp.com)
- Scientific visualization, high-performance computing (HPC), problem-solving environments, algorithms and software for multicore architectures, topology-aware MPI communications, and scalable checkpointing techniques. (sdsmt.edu)
- Frequency Recovery in Power Grids using High-Performance Computing. (ornl.gov)
Efficiency1
- Besides, we are interested in assessing its efficiency in several possible evolutionary settings, finding out what kind of behavior we can expect, and what can be done to improve it. (blogalia.com)
Search3
- The algorithms are Genetic Algorithm (GA), Tabu Search (TS) and, Evolutionary Tabu Search Algorithm (ETS). (actapress.com)
- Metaheuristic search algorithms with population-based frameworks are capable of handling optimization in high-dimensional real-world problems for several domains including imaging, IoT, smart manufacturing, and healthcare. (theiet.org)
- Towards a GPU Accelerated Selective Sparsity Multilayer Perceptron Algorithm using K-Nearest Neighbors Search. (ornl.gov)
Nature inspired1
- We have witnessed an explosion of research activity around nature-inspired computing and bio-inspired optimization techniques, which can provide powerful tools for solving learning problems and data analysis in very large data sets. (theiet.org)
Experimental2
- The experimental results show that the proposed algorithm is capable of improving the accuracy of K-means and decreasing the SSE of K-means, which indicates that the proposed algorithm can prevent K-means from falling into the local optimum to some extent. (techscience.com)
- As an attempt in this direction, this paper presents evidences to showcase the role of the Scale Factor (F) parameter of DE algorithm through the plots generated based on the studies made from experimental results obtained through a well formulated experimental setup. (amrita.edu)
Environments1
- Application and user centred intelligently orchestrated context aware ubiquitous and pervasive computing systems, environments and services. (essex.ac.uk)
Research3
- My research interest is mainly in Artificial Intelligence and optimization techniques in engineering specifically with the use of heuristic algorithms. (usp.ac.fj)
- Analysing and understanding the working nature of DE algorithm, for its further improvement, is an active research area in Evolutionary Computing (EC) field. (amrita.edu)
- Our research and education can therefore be characterized as being use-inspired and fundamental, ranging from developing new security and AI algorithms to engaging with real use cases of our partners. (tudelft.nl)
Systems3
- To deploy MapReduce as a data processing service over open systems such as service oriented architecture, cloud computing, and volunteer computing, we must provide necessary security mechanisms to protect the integrity of MapReduce data processing services. (ncsu.edu)
- I am interested in the development of user and task centred intelligently orchestrated and context aware pervasive computing systems. (essex.ac.uk)
- Cybersickness (visually induced motion sickness from a virtual environment), 3D systems, virtual reality (VR), user interfaces, and analysis of algorithms. (sdsmt.edu)
Design2
- Type-1 and Type-2 fuzzy system design and applications and hybrid techniques that include deep learning and evolutionary optimisation approaches. (essex.ac.uk)
- To design and implement optimization algorithms, several methods are used that bring superior performance. (theiet.org)
Cellular1
- Two basic models were introduced for this purpose, the island models, which are based on a division of the population into fixed subpopulations that exchange individuals from time to time, and the neighbourhood models, which assign individuals to overlapping neighbourhoods, also known as cellular genetic or evolutionary algorithms (cGA or cEA). (wikipedia.org)
Problems6
- Evolutionary meta-heuristics, which have demonstrated their usefulness in solving complex problems, have not been fully exploited yet in this context. (ssrn.com)
- Evolutionary algorithms (EAs) are known to be good solvers for optimization problems ubiquitous in various problem domains. (usp.ac.fj)
- This kind of algorithms solves those problems where problem formulation is either impossible or very time consuming to process. (usp.ac.fj)
- Consolidated Optimization Algorithm for Resource-constrained Project Scheduling Problems. (cinvestav.mx)
- To overcome these limitations and to solve efficiently large scale combinatorial and highly nonlinear optimization problems, more flexible and adaptable algorithms are necessary. (theiet.org)
- They explain how to better handle different kinds of uncertainties in real-life problems using state-of-art of machine learning algorithms. (theiet.org)
Applications4
- Subsequent researches made by various authors who have worked on this problem and a wide variety of models and algorithms have been developed in the related literature within a broad range of applications. (hindawi.com)
- Baker, J.E.: Genetic algorithms and their applications. (crossref.org)
- Computer science and computer scientists study computers, computing, the software and hardware in a computer, and their applications in our modern society. (sdsmt.edu)
- In software, we develop new algorithms for automated reverse engineering or analysis of applications. (tudelft.nl)
Data4
- In privacy, we develop advanced methods for homomorphic encryption and multi-party computing with application in data sharing and blockchain. (tudelft.nl)
- Examples include the development of learning algorithms that can handle large network data flows, deep learning methods that are immune to common side-channel defenses, machine learning algorithms that can operate on encrypted data, and analysis of the latest security threats. (tudelft.nl)
- QIM (the Center for Quantification of Imaging Data from Max IV) - a cross-border collaboration platform for 3D/4D imaging at large-scale imaging facilities, aimed at developing algorithms for quantitative image analysis. (lu.se)
- To these data we applied the evolutionary theory of task specialisation (ParetoTI) to identify and characterise distinct archetypes, i.e. molecular subtypes, of LNETs. (who.int)
Machine2
- Specializations: Artificial Intelligence (Al) and Machine Learning (ML), Cybersecurity, Visual and Interactive Computing. (sdsmt.edu)
- In hardware, we use machine learning to develop new attack mechanisms for side-channel analysis, and evolutionary algorithms to create improved hardware designs. (tudelft.nl)
Approaches1
- A recent systematic review of many such processes noted different methodological approaches including bibliometric indexes, Delphi techniques, Multi-Criteria Decision Analysis (MCDA), qualitative algorithms, and questionnaires. (who.int)
Methods1
- As both methods can quickly rank a large volume of pathogens, they generate an initial qualitative can be used to provide a short list for risk ranking using a more ranking for further study algorithm comprehensive technique. (who.int)
Nonlinear1
- To exploit the known linear theory, linearizations are used and bounds are computed to find the allowable noise for the nonlinear system. (ncsu.edu)