다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

Metaheuristic design of feedforward neural networks

Time-series forecasting is an important research and application area. Much effort has been devoted over the past several decades to develop and improve the time-series forecasting models. This paper introduces a new time-series forecasting model based on the flexible neural tree (FNT). The FNT model is generated initially as a flexible multi-layer feed-forward neural network and evolved using an evolutionary procedure. Very often it is a difficult task to select the proper input variables or time-lags for constructing a time-series model. Our research demonstrates that the FNT model is capable of handing the task automatically. The performance and effectiveness of the proposed method are evaluated using time series prediction problems and compared with those of related methods.

Time-series forecasting using flexible neural tree model

Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems

This paper proposes a new hybrid stochastic training algorithm using the recently proposed grasshopper optimization algorithm (GOA) for multilayer perceptrons (MLPs) neural networks. The GOA algorithm is an emerging technique with a high potential in tackling optimization problems based on its flexible and adaptive searching mechanisms. It can demonstrate a satisfactory performance by escaping from local optima and balancing the exploration and exploitation trends. The proposed GOAMLP model is then applied to five important datasets: breast cancer, parkinson, diabetes, coronary heart disease, and orthopedic patients. The results are deeply validated in comparison with eight recent and well-regarded algorithms qualitatively and quantitatively. It is shown and proved that the proposed stochastic training algorithm GOAMLP is substantially beneficial in improving the classification rate of MLPs.

An efficient hybrid multilayer perceptron neural network with grasshopper optimization

Graphical abstractDisplay Omitted HighlightsA heterogeneous flexible neural tree (FNT) for function approximation was proposed.FNT was studied under Pareto-based multiobjective genetic programming framework.A diversity-index was introduced to maintain diversity in genetic population.FNT was found competitive with other algorithm when cross validated over datasets.Evolutionary weighted ensemble of HFNTs further improved FNT performance. Machine learning algorithms are inherently multiobjective in nature, where approximation error minimization and model's complexity simplification are two conflicting objectives. We proposed a multiobjective genetic programming (MOGP) for creating a heterogeneous flexible neural tree (HFNT), tree-like flexible feedforward neural network model. The functional heterogeneity in neural tree nodes was introduced to capture a better insight of data during learning because each input in a dataset possess different features. MOGP guided an initial HFNT population towards Pareto-optimal solutions, where the final population was used for making an ensemble system. A diversity index measure along with approximation error and complexity was introduced to maintain diversity among the candidates in the population. Hence, the ensemble was created by using accurate, structurally simple, and diverse candidates from MOGP final population. Differential evolution algorithm was applied to fine-tune the underlying parameters of the selected candidates. A comprehensive test over classification, regression, and time-series datasets proved the efficiency of the proposed algorithm over other available prediction methods. Moreover, the heterogeneous creation of HFNT proved to be efficient in making ensemble system from the final population.

/pdf/ensemble-of-heterogeneous-flexible-neural-trees-using-2jarqunvt9.pdf

Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming

The Third International Conference on Intelligent Human Computer Interaction 2011 (IHCI 2011) was held at Charles University, Prague, Czech Republic from August 29 - August 31, 2011. This conference was third in the series, following IHCI 2009 and IHCI 2010 held in January at IIIT Allahabad, India. Human computer interaction is a fast growing research area and an attractive subject of interest for both academia and industry. There are many interesting and challenging topics that need to be researched and discussed. This book aims to provide excellent opportunities for the dissemination of interesting new research and discussion about presented topics. It can be useful for researchers working on various aspects of human computer interaction. Topics covered in this book include user interface and interaction, theoretical background and applications of HCI and also data mining and knowledge discovery as a support of HCI applications.

Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011

This volume contains papers presented at the 2nd International Afro-European Conference for Industrial Advancement -- AECIA 2015. The conference aimed at bringing together the foremost experts and excellent young researchers from Africa, Europe and the rest of the world to disseminate the latest results from various fields of engineering, information, and communication technologies. The topics, discussed at the conference, covered a broad range of domains spanning from ICT and engineering to prediction, modeling, and analysis of complex systems. The 2015 edition of AECIA featured a distinguished special track on prediction, modeling and analysis of complex systems -- Nostradamus, and special sessions on Advances in Image Processing and Colorization and Data Processing, Protocols, and Applications in Wireless Sensor Networks.

Vclav Snel

Papers

Metaheuristic design of feedforward neural networks

Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming

Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011

Proceedings of the Second International Afro-European Conference for Industrial Advancement AECIA 2015