International Journal of Computational Intelligence Systems

ISSN: 1875-6883
Volume 12, Issue 1, 2018
Serge Dolgikh
Pages: 1 - 12
In this study we investigate information processing in deep neural network models. We demonstrate that unsupervised training of autoencoder models of certain class can result in emergence of compact and structured internal representation of the input data space that can be correlated with higher...
Carlos Villaseñor, Nancy Arana-Daniel, Alma Y. Alanis, Carlos López-Franco, Esteban A. Hernandez-Vargas
Pages: 13 - 27
Artificial immune systems are metaheuristic algorithms that mimic the adaptive capabilities of the immune system of vertebrates. Since the 1990s, they have become one of the main branches of computer intelligence. However, there are still many competitive processes in the biological phenomena that...
Booma Devi Sekar, Jean-Baptiste Lamy, Nekane Larburu, Brigitte Séroussi, Gilles Guézennec, Jacques Bouaud, Naiara Muro, Hui Wang, Jun Liu
Pages: 28 - 38
Breast cancer is identified as the most common type of cancer in women worldwide with 1.6 million women around the world diagnosed every year. This prompts many active areas of research in identifying better ways to prevent, detect, and treat breast cancer. DESIREE is a European Union funded project,...
G. R. R. Bóbeda, E. F. Combarro, S. Mazza, L. I. Giménez, I. Díaz
Pages: 79 - 89
In order to define management and marketing strategies, farmers need adequate knowledge about future yield with the greatest possible accuracy and anticipation. In citrus orchards, greater variability and non-normality of yield distributions complicate the early estimation of fruit production. This...
Muhammad Akram, Maham Arshad, - Shumaiza
Pages: 90 - 107
Fuzzy rough set theory is a hybrid method that deals with vagueness and uncertainty emphasized in decision-making. In this research study, we apply the concept of fuzzy rough sets to graphs. We introduce the notion of fuzzy rough digraphs and describe some of their methods of construction. In particular,...
Julio Suarez-Paez, Mayra Salcedo-Gonzalez, M. Esteve, J. A. Gómez, C. Palau, I. Pérez-Llopis
Pages: 123 - 130
This paper shows the implementation of a prototype of street theft detector using the deep learning technique R- CNN (Region-Based Convolutional Network), applied in the Command and Control Information System (C2IS) of National Police of Colombia, the prototype is implemented using three models of...
Ivona Brajević, Predrag Stanimirović
Pages: 131 - 148
Firefly algorithm (FA) is a prominent metaheuristc technique. It has been widely studied and hence there are a lot of modified FA variants proposed to solve hard optimization problems from various areas. In this paper an improved chaotic firefly algorithm (ICFA) is proposed for solving global optimization...
Junyu Xuan, Jie Lu, Zheng Yan, Guangquan Zhang
Pages: 164 - 171
Reinforcement learning (RL) aims to resolve the sequential decision-making under uncertainty problem where an agent needs to interact with an unknown environment with the expectation of optimising the cumulative long-term reward. Many real-world problems could benefit from RL, e.g., industrial robotics,...