[go: up one dir, main page]

Qi et al., 2012 - Google Patents

Multi-objective immune algorithm with Baldwinian learning

Qi et al., 2012

View PDF
Document ID
5433853591574478820
Author
Qi Y
Liu F
Liu M
Gong M
Jiao L
Publication year
Publication venue
Applied Soft Computing

External Links

Snippet

By replacing the selection component, a well researched evolutionary algorithm for scalar optimization problems (SOPs) can be directly used to solve multi-objective optimization problems (MOPs). Therefore, in most of existing multi-objective evolutionary algorithms …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/02—Knowledge representation
    • G06N5/022—Knowledge engineering, knowledge acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063—Operations research or analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G06F17/5009—Computer-aided design using simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/18—Digital computers in general; Data processing equipment in general in which a programme is changed according to experience gained by the computer itself during a complete run; Learning machines

Similar Documents

Publication Publication Date Title
Qi et al. Multi-objective immune algorithm with Baldwinian learning
Goodwin et al. Real-time digital twin-based optimization with predictive simulation learning
Hu et al. FCAN-MOPSO: An improved fuzzy-based graph clustering algorithm for complex networks with multiobjective particle swarm optimization
Valdez et al. Modular neural networks architecture optimization with a new nature inspired method using a fuzzy combination of particle swarm optimization and genetic algorithms
Yu et al. Evolving artificial neural networks using an improved PSO and DPSO
Cao et al. A modified artificial bee colony approach for the 0-1 knapsack problem
Tan et al. A coevolutionary algorithm for rules discovery in data mining
Shim et al. Multi-objective optimization with estimation of distribution algorithm in a noisy environment
Niu et al. Towards the optimality of QoS-aware web service composition with uncertainty
Behrang et al. Assessment of electricity demand in Iran's industrial sector using different intelligent optimization techniques
Moh Ousellam et al. Directed hypergraph neural network: Building a predictive framework
Verbeeck et al. Multi-objective optimization with surrogate trees
Mani et al. Effect of Population Structures on Quantum‐Inspired Evolutionary Algorithm
Sharma et al. Software effort estimation with data mining techniques-A review
Tyagi et al. Applications of genetic algorithm in water resources management and optimization
Wu et al. Multi-population based univariate marginal distribution algorithm for dynamic optimization problems
Su et al. Implementation of a genetic algorithm on MD-optimal designs for multivariate response surface models
Cai et al. Memetic clonal selection algorithm with EDA vaccination for unconstrained binary quadratic programming problems
Ankaiah et al. Multi objective constrained optimisation of data envelopment analysis by differential evolution
Li et al. Enao: Evolutionary neural architecture optimization in the approximate continuous latent space of a deep generative model
Pandey Parameters quantification of genetic algorithm
Alagumathi et al. A Multi-objective Evolutionary Algorithm Based on Decomposition—Dynamic Resource Allocation with Mixture Model
Mo et al. Constrained multiobjective biogeography optimization algorithm
Barbosa et al. The use of coevolution and the artificial immune system for ensemble learning
Gómez-Iglesias et al. Distributed and asynchronous solver for large CPU intensive problems