Geetha N., Sankar A.

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 711-719, 2018, DOI:10.1080/10798587.2017.1309003

Abstract The routing protocol for an ad hoc network should be efficient in utilizing the available resources to prolong the network lifetime. A Multi Criterion Fuzzy based Energy Efficient Routing Protocol (MCFEER) for Ad hoc Networks selects the path on constraints like bandwidth, battery life, hop count and buffer occupancy. In the route discovery phase, fuzzy system is applied for optimal route selection by destination node leading to successful data transmission. Multiple stable paths are preserved in route cache for usage during the route maintenance phase. The results are competitive when compared with Power aware Energy Efficient Routing (PEER) protocol using… More >

U. Kanimozhi, D. Manjula

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 701-709, 2018, DOI:10.1080/10798587.2017.1307626

Abstract We are witnessing the era of big data computing where computing the resources is becoming the main bottleneck to deal with those large datasets. In the case of high-dimensional data where each view of data is of high dimensionality, feature selection is necessary for further improving the clustering and classification results. In this paper, we propose a new feature selection method, Incremental Filtering Feature Selection (IF2S) algorithm, and a new clustering algorithm, Temporal Interval based Fuzzy Minimal Clustering (TIFMC) algorithm that employs the Fuzzy Rough Set for selecting optimal subset of features and for effective grouping of large volumes of… More >

Serkan Ballı^a, Mustafa Tuker^b

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 693-699, 2018, DOI:10.1080/10798587.2017.1306968

Abstract Heterogeneous networks are environments where networks having different topologies and technologies can be connected. In an environment including more than one heterogeneous access network, selection of a bad network may lead to emergence of negative results such as high cost and poor service experience for the users. Ensuring the use of the most effective access network for the personal needs of individuals is a complex decision-making process. In the present study, a multicriteria decision-making system employing fuzzy logic was developed to evaluate and select network service providers in Turkey. Fuzzy logic was used for the criteria containing uncertain and unclear… More >

Young Hun Song^a, Suk Lee^a, Kyoung Nam Ha^b, Kyung Chang Lee^c

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 683-691, 2018, DOI:10.1080/10798587.2017.1302712

Abstract Recently, FlexRay was developed to replace the controller area network (CAN) protocol in the chassis network systems to provide high-speed data transmission as well as hardware redundancy for safety. However, FlexRay network design is more complicated than with CAN protocol, which has been an in-vehicle network (IVN) standard for car manufacturers for decades, because the FlexRay has many parameters such as the base cycle or slot lengths. To simplify the FlexRay network design and assist vehicle network designers in configuring a FlexRay network, this paper presents an automatic field bus exchange format (FIBEX) generation method for migration from the CAN… More >

Win-Chin Lin^a, Chin-Chia Wu^a, Kejian Yu^b, Yong-Han Zhuang^a, Shang-Chia Liu^c

Intelligent Automation & Soft Computing, Vol.24, No.4, pp. 671-681, 2018, DOI:10.1080/10798587.2017.1302711

Abstract Most research studies on scheduling problems assume that a job visits certain machines only one time. However, this assumption is invalid in some real-life situations. For example, a job may be processed by the same machine more than once in semiconductor wafer manufacturing or in a printed circuit board manufacturing machine. Such a setting is known as the “re-entrant flowshop”. On the other hand, the importance of learning effect present in many practical situations such as machine shop, in different branches of industry and for a variety of corporate activities, in shortening life cycles, and in an increasing diversity of… More >

Laith Sawaqed¹, Khaled S. Hatamleh^1,2, Mohammad A. Jaradat^1,2, Qais Khasawneh^1,3

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 507-515, 2018, DOI:10.31209/2018.100000039

Abstract Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum power consumption. For that purpose,… More >

Changjiang Liu¹, Xuling Wu², Bing Mo¹, Yi Zhang³

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 671-678, 2018, DOI:10.31209/2018.100000033

Abstract With continuing commercialization of remote sensing satellites, the high resolution remote sensing image has been increasingly used in various fields of our life. However, processing technology of high resolution remote sensing images is still a tough problem. How to extract useful information from the massive information in high resolution remote sensing images is significant to the subsequent process. A multi-phase oil tank recognition of remote sensing images, namely coarse detection and artificial neural network (ANN) recognition, is proposed. The experimental results of algorithms presented in this paper show that the proposed processing technology is reliable and effective. More >

Wei Qin, Xiangfeng Luo

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 653-661, 2018, DOI:10.31209/2018.100000032

Abstract Concept learning has attracted considerable attention as a means to tackle problems of representation and learning corpus knowledge. In this paper, we investigate a challenging problem to automatically construct a patent concept learning model. Our model consists of two main processes; which is the acquisition of the initial concept graph and refined process for the initial concept graph. The learning algorithm of a patent concept graph is designed based on the Association Link Network (ALN). A concept is usually described by multiple documents utilizing ALN here in concept learning. We propose a mixture-ALN, which add links between documents and the… More >

Lin Gao, Mingzhen Wang

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 643-651, 2018, DOI:10.31209/2018.100000031

Abstract With the rapid development of the petrochemical industry, the number of largescale oil storage tanks has increased significantly, and many storage tanks are located in potential seismic regions. It is very necessary to analyze seismic response of oil storage tanks since their damage in an earthquake can lead to serious disasters and losses. In this paper, three models of vertical cylindrical oil storage tank in different sizes, which are commonly used in practical engineering are established. The dynamic characteristics, sloshing wave height and hydrodynamic pressure of the oil tank considering the liquid-structure coupling effect are analyzed by using ADINA finite… More >

Ling Wu¹, Haoxue Liu², Tong Zhu², Yueqi Hu³

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 633-642, 2018, DOI:10.31209/2018.100000030

Abstract The objective of the current study was to examine how experienced and inexperienced driver behaviour changed (including heart rate and longitudinal speeds) when approaching and exiting highway tunnels. Simultaneously, the NARX neural network was used to predict real-time speed with the heart rate regarded as the input variable. The results indicated that familiarity with the experimental route did decrease drivers’ mental stress but resulted in higher speed. The proposed NARX model could predict synchronous speed with high accuracy. These results of the present study concern how to establish the automated driver model in the simulation environment. More >