Search Results - (( developing models (evolutionary OR evolution) algorithm ) OR ( java implication new algorithm ))
Search alternatives:
- developing models »
- java implication »
- implication new »
- new algorithm »
-
1
Nature-Inspired cognitive evolution to play Ms. Pac-Man
Published 2011“…On the other hand, an evolutionary algorithm is to simulate the biological evolutionary processes that evolve potential solutions in order to solve the problems or tasks by applying the genetic operators such as crossover, mutation and selection into the solutions. …”
Get full text
Get full text
Get full text
Article -
2
Pareto ensembles for evolutionary synthesis of Neurocontrollers in a 2D maze-based video game
Published 2013“…A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
Get full text
Get full text
Article -
3
Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…Two multi-objective fed-batch models are also used as case studies to verify the performance of the proposed algorithm. …”
Get full text
Get full text
Thesis -
4
Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia
Published 2024“…Principle component analysis was used to determine which predictors were most reliable. Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. …”
Article -
5
Pareto Ensembles for evolutionary Synthesis of Neurocontrollers in a 2D Maze-based video game
Published 2013“…A system using multi-objective evolutionary algorithm is developed, which is called as Pareto Archived Evolution Strategy Neural Network(PAESNet), with the attempt to find a set of Pareto optimal solutions by simultaneously optimizing two conflicting objectives. …”
Get full text
Get full text
Article -
6
Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
Get full text
Get full text
Get full text
Get full text
Article -
7
Software testing optimization for large systems using agent-based and NSGA-II algorithms
Published 2023“…The performance of a multi-objective Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and evolutionary multi-agent system (EMAS) on Feature Models (FMs) to enhance large System testing is reported in this study.…”
Get full text
Get full text
Get full text
Article -
8
Mobile game application development using evolutionary algorithms
Published 2014“…Hence it has opened up a whole new market with its mass among users and attracted a large number of smartphone application developers. Evolutionary Algorithms have never been used on mobile applications, thus it gives a novel idea of utilizing Evolutionary Algorithms in developing applications typically in games for mobile platforms. …”
Get full text
Get full text
Get full text
Thesis -
9
-
10
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
Get full text
Get full text
Get full text
Get full text
Article -
11
Implementation of Evolutionary Algorithms to Parametric Identification of Gradient Flexible Plate Structure
Published 2023“…This paper focused on modelling of a gradient flexible plate system utilizing an evolutionary algorithm, namely particle swarm optimization (PSO) and cuckoo search (CS) algorithm. …”
Get full text
Get full text
Get full text
Article -
12
Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…On the other hand, an evolutionary algorithm has proven its effectiveness in searching the best feature subsets. …”
Get full text
Get full text
Get full text
Article -
13
INTELLIGENT MODELLING OF GRADIENT FLEXIBLE PLATE STRUCTURE UTILISING HYBRID EVOLUTIONARY ALGORITHM
Published 2023“…The research utilised parametric system identification based on autoregressive with exogenous input (ARX) model structure. First, evolutionary algorithms, namely particle swarm optimisation (PSO) and grey wolf optimisation (GWO) were used in developing GFPS dynamic model and their performances were compared. …”
Get full text
Get full text
Thesis -
14
Towards Software Product Lines Optimization Using Evolutionary Algorithms
Published 2019“…We report on the problem encoding, variation operators and different types of algorithms: Indicator Based Evolutionary Algorithm (IBEA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), Multi-Objective Evolutionary Algorithms based on Decomposition (MOEA/D) and Strength Pareto Evolutionary algorithm II (SPEA-II). …”
Get full text
Get full text
Proceeding Paper -
15
-
16
The Development And Application Of Evolutionary Computation-Based Layered Encoding Cascade Optimization Model
Published 2010“…In the proposed model, particular attention is given to genetic algorithm (GA) and particle swarm optimization (PSO) in the development of evolutionary-based search mechanism.…”
Get full text
Get full text
Thesis -
17
Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…The methodology will be tested on developed synthetic model.…”
Get full text
Get full text
Final Year Project -
18
Evolutionary Algorithms In Auction Models Of Service Procurement
Published 2019Get full text
Get full text
Thesis -
19
Time series forecasting of energy commodity using grey wolf optimizer
Published 2015“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
Get full text
Get full text
Get full text
Conference or Workshop Item -
20
Parameter extraction of solar photovoltaic modules using penalty-based differential evolution
Published 2012“…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
Get full text
Get full text
Article
