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  • Open Access


    Intelligence-based Channel Equalization for 4x1 SFBC-OFDM Receiver

    Divneet Singh Kapoor1,*, Amit Kumar Kohli2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 439-446, 2020, DOI:10.32604/iasc.2020.013920

    Abstract This research paper represents an intelligent receiver based on the artificial-neuralnetworks (ANNs) for a 4x1 space-frequency-block-coded orthogonal-frequencydivision-multiplexing (SFBC-OFDM) system, working under slow time-varying frequency-selective fading channels. The proposed equalizer directly recovers transmitted symbols from the received signal, without the explicit requirement of the channel estimation. The ANN based equalizer is modelled by using feedforward as well as the recurrent neural-network (NN) architectures, and is trained using error backpropagation algorithms. The major focus is on efficiency and efficacy of three different strategies, namely the gradient-descent with momentum (GDM), resilient-propagation (RProp), and Levenberg-Marquardt (LM) algorithms. The recurrent More >

  • Open Access


    A Novel WSN-Oriented Locating Approach Based on Density

    T. Zhang1,2, D. G. Zhang1,2,*, X. H. Liu1,2, C. L. Gong1,2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 429-437, 2020, DOI:10.32604/iasc.2020.013919

    Abstract It is known that the locating accuracy of the traditional Distance Vector-HOP (DV-HOP) approach in a Wireless Sensor Network (WSN) depends on the density of the anchor node. A novel WSN-oriented locating approach based on a node's density is proposed in this paper. The approach can compute the distance of the node based on the maximum likelihood estimation strategy. It can improve the accuracy ratio of the measuring distance among the nodes. The relative nodes of a WSN can find the average hop distances by estimating the distances from themselves to their circular nodes. In More >

  • Open Access


    Extreme Learning Machine with Elastic Net Regularization

    Lihua Guo*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 421-427, 2020, DOI:10.32604/iasc.2020.013918

    Abstract Compared with deep neural learning, the extreme learning machine (ELM) can be quickly converged without iteratively tuning hidden nodes. Inspired by this merit, an extreme learning machine with elastic net regularization (ELM-EN) is proposed in this paper. The elastic net is a regularization method that combines LASSO and ridge penalties. This regularization can keep a balance between system stability and solution's sparsity. Moreover, an excellent optimization method, i.e., accelerated proximal gradient, is used to find the minimum of the system optimization function. Various datasets from UCI repository and two facial expression image datasets are used More >

  • Open Access


    Optimized PID Controller Using Adaptive Differential Evolution with Meanof-pbest Mutation Strategy

    Ti-Hung Chen1, Ming-Feng Yeh2,*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 407-420, 2020, DOI:10.32604/iasc.2020.013917

    Abstract On the basis of JADE (adaptive differential evolution with optional external archive) and the modified differential evolution with p-best crossover (MDE_pBX), this study attempts to propose a modified mutation strategy termed "DE/(pbest)/1" for the differential evolution (DE) algorithm, where “(pbest)” represents the mean of p top-best vectors. Two modified parameter adaptation mechanisms are also proposed to update the crossover rate and the scale factor, respectively, in an adaptive manner. The DE variant with the proposed mutation strategy and two modified adaptation mechanisms is termed adaptive differential evolution with mean-of-pbest mutation strategy, denoted by ADE_pBM is comparable to or More >

  • Open Access


    Automated Inspection of Char Morphologies in Colombian Coals Using Image Analysis

    Deisy Chaves1,5,*, Maria Trujillo1, Edward Garcia2, Juan Barraza2, Edward Lester3, Maribel Barajas4, Billy Rodriguez4, Manuel Romero4, Laura Fernández-Robles5

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 397-405, 2020, DOI:10.32604/iasc.2020.013916

    Abstract Precise automated determination of char morphologies formed by coal during combustion can lead to more efficient industrial control systems for coal combustion. Commonly, char particles are manually classified following the ICCP decision tree which considers four morphological features. One of these features is unfused material, and this class of material not characteristic of Colombian coals. In this paper, we propose new machine learning algorithms to classify the char particles in an image based system. Our hypothesis is that supervised classification methods can outperform the 4 ‘class’ ICCP criteria. In this paper we evaluate several morphological More >

  • Open Access


    Genetic Algorithm and Tabu Search Memory with Course Sandwiching (GATS_CS) for University Examination Timetabling

    Abayomi-Alli A.1, Misra S.2,3, Fernández-Sanz L.4, Abayomi-Alli O.2,*, Edun A. R.1

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 385-396, 2020, DOI:10.32604/iasc.2020.013915

    Abstract University timetable scheduling is a complicated constraint problem because educational institutions use timetables to maximize and optimize scarce resources, such as time and space. In this paper, an examination timetable system using Genetic Algorithm and Tabu Search memory with course sandwiching (GAT_CS), was developed for a large public University. The concept of Genetic Algorithm with Selection and Evaluation was implemented while the memory properties of Tabu Search and course sandwiching replaced Crossover and Mutation. The result showed that GAT_CS had hall allocation accuracies of 96.07% and 99.02%, unallocated score of 3.93% and 0.98% for first More >

  • Open Access


    A Progressive Output Strategy for Real-time Feedback Control Systems

    Qiming Zou1, Ling Wang1, *, Jie Liu1, Yingtao Jiang2

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 631-639, 2020, DOI:10.32604/iasc.2020.012549

    Abstract The real-time requirements imposed on a feedback control system are often hard to be met, as the controller spends a disproportionately large amount of time waiting for a control cycle to reach its final state. When such a final state is established, multiple tasks have to be prioritized and launched altogether simultaneously, and the system is given an extremely short time window to generate its output. This huge gap between the wait and action times, perceived as a load unbalancing problem, hinders a control decision to be made in real time. To address this challenging… More >

  • Open Access


    Reliable Approximated Number System with Exact Bounds and Three-Valued Logic

    Reeseo Cha1, Wonhong Nam2,*, Jin-Young Choi1

    Computer Systems Science and Engineering, Vol.33, No.6, pp. 447-455, 2018, DOI:10.32604/csse.2018.33.447

    Abstract Many programming languages provides mechanism to guarantee the error ranges of exact numbers and intervals. However, when they are integrated with unreliable approximated numbers, we cannot rely on the error-ranges anymore. Such unreliable error-ranges may cause serious errors in programs, and especially in safety critical systems they cost us huge amount of money and/or threaten human’s life. Hence, in this paper, we propose a novel number system to safely perform arithmetic operations with guaranteed error ranges. In the number system, exact numbers are separated from approximated numbers, and approximated numbers with strictly guaranteed error-ranges are More >

  • Open Access


    A Phoneme-Based Approach for Eliminating Out-of-vocabulary Problem Turkish Speech Recognition Using Hidden Markov Model

    Erdem Yavuz1,∗, Vedat Topuz2

    Computer Systems Science and Engineering, Vol.33, No.6, pp. 429-445, 2018, DOI:10.32604/csse.2018.33.429

    Abstract Since Turkish is a morphologically productive language, it is almost impossible for a word-based recognition system to be realized to completely model Turkish language. Due to the fact that it is difficult for the system to recognize words not introduced to it in a word-based recognition system, recognition success rate drops considerably caused by out-of-vocabulary words. In this study, a speaker-dependent, phoneme-based word recognition system has been designed and implemented for Turkish Language to overcome the problem. An algorithm for finding phoneme-boundaries has been devised in order to segment the word into its phonemes. After More >

  • Open Access


    Energy Aware Routing Algorithm in Manet Using Linear Programming

    Hany Ramadan1,∗, Ben Bella S. Tawfik2, Alaa El Din M. Riad3

    Computer Systems Science and Engineering, Vol.33, No.6, pp. 421-428, 2018, DOI:10.32604/csse.2018.33.421

    Abstract Mobile ad hoc networks (MANET) are wireless network without infrastructure and suffering from low power battery. Therefore the main objective in finding a route for traffic transfer from a given source to a given destination is to minimize the node energy consumption. This paper solves the problem of finding a route satisfying the main objective of minimum energy consumption and other QoS requirements such as minimum delay and maximum packet delivery ratio by using linear programming technique. Two cases are considered: 1. The traffic amount of a given request is transmitted into single path, and… More >

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