Page
%P
19 Result(s)
within
Viviana Cocco Mariani
-
Article
Variational mode decomposition and bagging extreme learning machine with multi-objective optimization for wind power forecasting
A wind power forecast is an useful support tool for planning and operating wind farm production, facilitating decisions regarding maintenance and load share. This paper presents an evaluation of a cooperative ...
-
Article
Web pages from mockup design based on convolutional neural network and class activation map**
The objective of this study is to validate the use of Deep Neural Networks (DNNs) to segment and classify web elements. To achieve this, a dataset of 2200 images was created through screenshots of real web pag...
-
Article
A comprehensive review on Jaya optimization algorithm
The Jaya Algorithm is a relatively new population-based optimization, which has become a progressively valuable tool in swarm intelligence. The Jaya algorithm incorporates the survival of the fittest principle...
-
Article
Optimization of operating conditions of the Fischer–Tropsch synthesis based on multi-objective differential evolution algorithm
A study on the Fischer–Tropsch synthesis was investigated employing a one-dimensional non-isothermal model in a fixed-bed reactor over a Co/Al2O3 catalyst. The reaction kinetic follows a semi-empirical approach. ...
-
Article
Extreme gradient boosting model based on improved Jaya optimizer applied to forecasting energy consumption in residential buildings
A great number of prediction methods have been proposed in the past several decades for residential building energy consumption prediction. In this paper, the proposed machine learning model allows the predict...
-
Chapter
Ensemble Learning Models Coupled with Urban Mobility Information Applied to Predict COVID-19 Incidence Cases
The coronavirus disease (COVID-19), according to the World Health Organization, by July 15th, 2021, has infected more than 188 million people, and more than 4 millions have died from it in the worldwide. It is...
-
Article
Self-adaptive differential evolution applied to combustion engine calibration
In this paper, a new population-based stochastic optimization algorithm called Hybrid Self-Adaptive Differential Evolution (HSADE) is proposed. The algorithm addresses unconstrained global optimization problem...
-
Article
On the use of particle-wall interaction models to predict particle-laden flow in 90-deg bends
The objective of this work is to evaluate the capability of different combinations of a turbulence model and a Lagrangian particle tracking (LPT) model integrating a particle-wall interaction (PWI) model to pr...
-
Article
Design of spiral heat exchanger from economic and thermal point of view using a tuned wind-driven optimizer
This paper presents an optimization of spiral heat exchangers by wind-driven optimization and a novel variant of this algorithm by the insertion of a statistic distribution to self-adapting of the evolution pa...
-
Article
Radiative heat transfer considering the effect of multiple reflections in greenhouse structures
In greenhouse structures, given the major role played by glazing systems with regard to losses and gains of energy in the system, an accurate prediction of the radiative heat transfer through the glazing mater...
-
Chapter and Conference Paper
Artificial Immune Network Approach with Beta Differential Operator Applied to Optimization of Heat Exchangers
The artificial immune systems combine these strengths have been gaining significant attention due to its powerful adaptive learning and memory capabilities. A meta-heuristic approach called opt-aiNET (artifici...
-
Book
-
Chapter
PSO in Building Fuzzy Systems
In this chapter, we take advantage of particle swarm optimization to build fuzzy systems automatically for different kinds of problems by simply providing the objective function and the problem variables. Part...
-
Chapter
Reliability-Redundancy Optimization Using a Chaotic Differential Harmony Search Algorithm
In many industrial systems, reliability has been considered as an important design measure. In this context, the system reliability maximization subject to performance and cost constraints is well known as rel...
-
Chapter
A Discrete Differential Evolution Approach with Local Search for Traveling Salesman Problems
Combinatorial optimization problems are very commonly seen in scientific research and practical applications. Traveling Salesman Problem (TSP) is one nonpolynomial-hard combinatorial optimization problem. It c...
-
Chapter and Conference Paper
Artificial Immune Network Combined with Normative Knowledge for Power Economic Dispatch of Thermal Units
Recently, many research activities have been devoted to Artificial Immune Systems (AISs). AISs use ideas gleaned from immunology to develop intelligent systems capable of learning and adapting. AISs are optimi...
-
Chapter
Self-adaptive Differential Evolution Using Chaotic Local Search for Solving Power Economic Dispatch with Nonsmooth Fuel Cost Function
The differential evolution (DE), proposed by Storn and Price, is a powerful population-based algorithm of evolutionary computation field designed for solving global optimization problems. The advantages of DE ...
-
Chapter and Conference Paper
Combining of Differential Evolution and Implicit Filtering Algorithm Applied to Electromagnetic Design Optimization
Differential evolution (DE) is a population-based and stochastic search algorithm of evolutionary computation that offers three major advantages: it finds the global minimum regardless of the initial parameter...
-
Chapter and Conference Paper
A Hybrid Method of Differential Evolution and SQP for Solving the Economic Dispatch Problem with Valve-Point Effect
The differential evolution (DE) is an improved version of evolution strategies and Nelder-Mead simplex methods. DE has been successfully applied in various fields, such as optimization nonlinear functions, mul...
