Leo Raju^a, R. S. Milton^b, Senthilkumaran Mahadevan^a

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 483-491, 2018, DOI:10.1080/10798587.2017.1305647

Abstract The objective of this paper is to monitor and control a micro-grid model developed in MATLABSimulink through Multi Agent System (MAS) for autonomous and distributed energy management. Since MATLAB/Simulink is not compatible with parallel operations of MAS, MAS operating in Java Agent Development Environment (JADE) is linked with MATLAB/Simulink through Multi Agent Control using Simulink with Jade extension (MACSimJX). This allows the micro-grid system designed with Simulink to be controlled by MAS for realizing the advantages of MAS in distributed and decentralized microgrid systems. JADE agents receive environmental information through Simulink and they coordinate to take best possible action, which… More >

Noé G. Aldana-Murillo, Jean-Bernard Hayet, Héctor M. Becerra

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 471-481, 2018, DOI:10.1080/10798587.2017.1304508

Abstract In this paper, we address the problem of the appearance-based localization of a humanoid robot, in the context of robot navigation. We only use information obtained by a single sensor, in this case the camera mounted on the robot. We aim at determining the most similar image within a previously acquired set of key images (also referred to as a visual memory) to the current view of the monocular camera carried by the robot. The robot is initially kidnapped and the current image has to be compared with the visual memory. To solve this problem, we rely on a hierarchical… More >

Nancy Arana-Daniel, Carlos Villaseñor, Carlos López-Franco, Alma Y. Alanís, Roberto Valencia-Murillo

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 461-467, 2018, DOI:10.1080/10798587.2017.1299356

Abstract Structure from Motion algorithms offer good advantages, such as extract 3D information in monocular systems and structures estimation as shown in Hartley & Zisserman for numerous applications, for instance; augmented reality, autonomous navigation, motion capture, remote sensing and object recognition among others. Nevertheless, this algorithm suffers some weaknesses in precision. In the present work, we extent the proposal in Arana-Daniel, Villaseñor, López-Franco, & Alanís that presents a new strategy using bio-inspired intelligence algorithm and Conformal Geometric Algebra, based in the object mapping paradigm, to overcome the accuracy problem in two-view Structure form motion algorithms. For this instance, we include two… More >

Imed Kacem, Ahmed Kadri, Pierre Laroche

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 421-430, 2018, DOI:10.31209/2018.100000016

Abstract This paper addresses an inventory regulation problem in bicycle sharingsystems. The problem is to balance a network consisting of a set of stations by using a single vehicle, with the aim of minimizing the weighted sum of the waiting times during which some stations remain imbalanced. Motivated by the complexity of this problem, we propose a two-stage procedure based on decomposition. First, the network is divided into multiple zones by using two different clustering strategies. Then, the balancing problem is solved in each zone. Finally, the order in which the zones must be visited is defined. To solve these problems,… More >

Qais A. Khasawneh^1,3, Mohammad Abdel Kareem Jaradat^1,2, Mohammad Al-Shabi⁴, Hala Khalaf¹

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 443-457, 2018, DOI:10.31209/2018.100000008

Abstract This work presents a new micro-positioning system that is implemented in an inchworm robot to move into desired locations. The system consists of four-bar mechanism; one link is fixed, and each one of the remaining links carries a piezoelectric actuator (PZT). PZTs are specifically chosen since they provide fast response and small displacements; up to ±30 µm for ±100 Volts. The system’s mathematical model is derived and is numerically simulated by MATLAB. Three fuzzy PI controllers, which are tuned automatically by genetic algorithm, are designed to control the system. Results indicate an error of less than 1% although disturbances present. More >

Carlos Lopez-Franco¹, Javier Gomez-Avila², Nancy Arana-Daniel³, Alma Y. Alanis

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 431-442, 2018, DOI:10.31209/2018.100000000

Abstract This paper presents a method for 3D pose estimation using visual information and a soft-computing algorithm. The algorithm uses quaternions to represent rotations, and Particle Swarm Optimization to estimate such quaternion. The rotation estimation problem is cast as a minimization problem, which finds the best quaternion for the given data using the PSO algorithm. With this technique, the algorithm always returns a valid quaternion, and therefore a valid rotation. During the estimation process, the algorithm is able to detect and reject outliers. The simulations and experimental results show the robustness of algorithm against noise and outliers. More >

Kazim Sari

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 405-412, 2018, DOI:10.1080/10798587.2017.1352258

Abstract Nowadays, there has been a great interest for business enterprises to work together or collaborate in the supply chain. It is thus possible for them to gain a competitive advantage in the marketplace. However, determining the right collaboration strategy is not an easy task. Namely, there are several factors that need to be considered at the same time. In this regard, an expert system based on fuzzy rules is proposed to choose an appropriate collaboration strategy for a given supply chain. To this end, firstly, the factors that are significant for supply chain collaboration are extracted via an extensive review… More >

Qian Wang^a,b,c, Jiadong Ren^a,b, Darryl N Davis^c, Yongqiang Cheng^c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 399-404, 2018, DOI:10.1080/10798587.2017.1340135

Abstract Frequent pattern mining usually requires much run time and memory usage. In some applications, only the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of the results is even more important than time and memory consumption. A Frequent Pattern algorithm for mining Top-rank-K patterns, FP_TopK, is proposed. It is based on a Node-list data structure extracted from FTPP-tree. Each node is with one or more triple sets, which contain supports, preorder and postorder transversal orders for candidate pattern generation and top-rank-k frequent pattern mining. FP_ TopK uses the minimal support threshold for pruning strategy… More >

Amin Mohajer^a, Morteza Barari^a, Houman Zarrabi^b

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 413-420, 2018, DOI:10.1080/10798587.2017.1312893

Abstract It is essential to satisfy class-specific QoS constraints to provide broadband services for new generation wireless networks. A self-optimization technique is introduced as the only viable solution for controlling and managing this type of huge data networks. This technique allows control of resources and key performance indicators without human intervention, based solely on the network intelligence. The present study proposes a big data based self optimization networking (BD-SON) model for wireless networks in which the KPI parameters affecting the QoS are assumed to be controlled through a multidimensional decision-making process. Also, Resource Management Center (RMC) was used to allocate the… More >

Liang Wang^a,b, Jiping Liu^a,b, Shenghua Xu^b, Jinjin Dong^c, Yi Yang^d

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 391-398, 2018, DOI:10.1080/10798587.2017.1296660

Abstract Forest biomass is a significant indicator for substance accumulation and forest succession, and can provide valuable information for forest management and scientific planning. Accurate estimations of forest biomass at a fine resolution are important for a better understanding of the forest productivity and carbon cycling dynamics. In this study, considering the low efficiency and accuracy of the existing biomass estimation models for remote sensing data, Landsat 8 OLI imagery and field data cooperated with the radial basis function artificial neural network (RBF ANN) approach is used to estimate the forest Above Ground Biomass (AGB) in the Mount Tai area, Shandong… More >