Next Issue
Previous Issue

Table of Contents

Algorithms, Volume 11, Issue 3 (March 2018)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
View options order results:
result details:
Displaying articles 1-10
Export citation of selected articles as:

Editorial

Jump to: Research

Open AccessEditorial Special Issue on Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition
Algorithms 2018, 11(3), 25; doi:10.3390/a11030025
Received: 22 February 2018 / Revised: 22 February 2018 / Accepted: 24 February 2018 / Published: 28 February 2018
PDF Full-text (164 KB) | HTML Full-text | XML Full-text
Abstract
This special issue of Algorithms is devoted to the study of Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. The special issue considered both theoretical contributions able to advance the state-of-the-art in this field and practical applications that describe
[...] Read more.
This special issue of Algorithms is devoted to the study of Computational Intelligence and Nature-Inspired Algorithms for Real-World Data Analytics and Pattern Recognition. The special issue considered both theoretical contributions able to advance the state-of-the-art in this field and practical applications that describe novel approaches for solving real-world problems. Full article

Research

Jump to: Editorial

Open AccessArticle A Class of Algorithms for Continuous Wavelet Transform Based on the Circulant Matrix
Algorithms 2018, 11(3), 24; doi:10.3390/a11030024
Received: 20 November 2017 / Revised: 6 February 2018 / Accepted: 22 February 2018 / Published: 27 February 2018
PDF Full-text (4087 KB) | HTML Full-text | XML Full-text
Abstract
The Continuous Wavelet Transform (CWT) is an important mathematical tool in signal processing, which is a linear time-invariant operator with causality and stability for a fixed scale and real-life application. A novel and simple proof of the FFT-based fast method of linear convolution
[...] Read more.
The Continuous Wavelet Transform (CWT) is an important mathematical tool in signal processing, which is a linear time-invariant operator with causality and stability for a fixed scale and real-life application. A novel and simple proof of the FFT-based fast method of linear convolution is presented by exploiting the structures of circulant matrix. After introducing Equivalent Condition of Time-domain and Frequency-domain Algorithms of CWT, a class of algorithms for continuous wavelet transform are proposed and analyzed in this paper, which can cover the algorithms in JLAB and WaveLab, as well as the other existing methods such as the c w t function in the toolbox of MATLAB. In this framework, two theoretical issues for the computation of CWT are analyzed. Firstly, edge effect is easily handled by using Equivalent Condition of Time-domain and Frequency-domain Algorithms of CWT and higher precision is expected. Secondly, due to the fact that linear convolution expands the support of the signal, which parts of the linear convolution are just the coefficients of CWT is analyzed by exploring the relationship of the filters of Frequency-domain and Time-domain algorithms, and some generalizations are given. Numerical experiments are presented to further demonstrate our analyses. Full article
Figures

Figure 1

Open AccessArticle A Novel Evolutionary Algorithm for Designing Robust Analog Filters
Algorithms 2018, 11(3), 26; doi:10.3390/a11030026
Received: 12 November 2017 / Revised: 24 February 2018 / Accepted: 27 February 2018 / Published: 1 March 2018
PDF Full-text (674 KB) | HTML Full-text | XML Full-text
Abstract
Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness
[...] Read more.
Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological structure of a system may set a limit on the robustness achievable through parameter tuning. This paper proposes a new evolutionary algorithm for robust design that exploits the open-ended topological search capability of genetic programming (GP) coupled with bond graph modeling. We applied our GP-based robust design (GPRD) algorithm to evolve robust lowpass and highpass analog filters. Compared with a traditional robust design approach based on a state-of-the-art real-parameter genetic algorithm (GA), our GPRD algorithm with a fitness criterion rewarding robustness, with respect to parameter perturbations, can evolve more robust filters than what was achieved through parameter tuning alone. We also find that inappropriate GA tuning may mislead the search process and that multiple-simulation and perturbed fitness evaluation methods for evolving robustness have complementary behaviors with no absolute advantage of one over the other. Full article
Figures

Open AccessArticle Spectrum Allocation Based on an Improved Gravitational Search Algorithm
Algorithms 2018, 11(3), 27; doi:10.3390/a11030027
Received: 8 November 2017 / Revised: 1 March 2018 / Accepted: 2 March 2018 / Published: 5 March 2018
PDF Full-text (6302 KB) | HTML Full-text | XML Full-text
Abstract
In cognitive radio networks (CRNs), improving system utility and ensuring system fairness are two important issues. In this paper, we propose a spectrum allocation model to construct CRNs based on graph coloring theory, which contains three classes of matrices: available matrix, utility matrix,
[...] Read more.
In cognitive radio networks (CRNs), improving system utility and ensuring system fairness are two important issues. In this paper, we propose a spectrum allocation model to construct CRNs based on graph coloring theory, which contains three classes of matrices: available matrix, utility matrix, and interference matrix. Based on the model, we formulate a system objective function by jointly considering two features: system utility and system fairness. Based on the proposed model and the objective problem, we develop an improved gravitational search algorithm (IGSA) from two aspects: first, we introduce the pattern search algorithm (PSA) to improve the global optimization ability of the original gravitational search algorithm (GSA); second, we design the Chebyshev chaotic sequences to enhance the convergence speed and precision of the algorithm. Simulation results demonstrate that the proposed algorithm achieves better performance than traditional methods in spectrum allocation. Full article
Figures

Figure 1

Open AccessArticle Modified Convolutional Neural Network Based on Dropout and the Stochastic Gradient Descent Optimizer
Algorithms 2018, 11(3), 28; doi:10.3390/a11030028
Received: 25 December 2017 / Revised: 5 March 2018 / Accepted: 5 March 2018 / Published: 7 March 2018
PDF Full-text (3376 KB) | HTML Full-text | XML Full-text
Abstract
This study proposes a modified convolutional neural network (CNN) algorithm that is based on dropout and the stochastic gradient descent (SGD) optimizer (MCNN-DS), after analyzing the problems of CNNs in extracting the convolution features, to improve the feature recognition rate and reduce the
[...] Read more.
This study proposes a modified convolutional neural network (CNN) algorithm that is based on dropout and the stochastic gradient descent (SGD) optimizer (MCNN-DS), after analyzing the problems of CNNs in extracting the convolution features, to improve the feature recognition rate and reduce the time-cost of CNNs. The MCNN-DS has a quadratic CNN structure and adopts the rectified linear unit as the activation function to avoid the gradient problem and accelerate convergence. To address the overfitting problem, the algorithm uses an SGD optimizer, which is implemented by inserting a dropout layer into the all-connected and output layers, to minimize cross entropy. This study used the datasets MNIST, HCL2000, and EnglishHand as the benchmark data, analyzed the performance of the SGD optimizer under different learning parameters, and found that the proposed algorithm exhibited good recognition performance when the learning rate was set to [0.05, 0.07]. The performances of WCNN, MLP-CNN, SVM-ELM, and MCNN-DS were compared. Statistical results showed the following: (1) For the benchmark MNIST, the MCNN-DS exhibited a high recognition rate of 99.97%, and the time-cost of the proposed algorithm was merely 21.95% of MLP-CNN, and 10.02% of SVM-ELM; (2) Compared with SVM-ELM, the average improvement in the recognition rate of MCNN-DS was 2.35% for the benchmark HCL2000, and the time-cost of MCNN-DS was only 15.41%; (3) For the EnglishHand test set, the lowest recognition rate of the algorithm was 84.93%, the highest recognition rate was 95.29%, and the average recognition rate was 89.77%. Full article
(This article belongs to the Special Issue Advanced Artificial Neural Networks)
Figures

Figure 1

Open AccessArticle Dombi Aggregation Operators of Neutrosophic Cubic Sets for Multiple Attribute Decision-Making
Algorithms 2018, 11(3), 29; doi:10.3390/a11030029
Received: 7 February 2018 / Revised: 2 March 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
PDF Full-text (782 KB) | HTML Full-text | XML Full-text
Abstract
The neutrosophic cubic set can describe complex decision-making problems with its single-valued neutrosophic numbers and interval neutrosophic numbers simultaneously. The Dombi operations have the advantage of good flexibility with the operational parameter. In order to solve decision-making problems with flexible operational parameter under
[...] Read more.
The neutrosophic cubic set can describe complex decision-making problems with its single-valued neutrosophic numbers and interval neutrosophic numbers simultaneously. The Dombi operations have the advantage of good flexibility with the operational parameter. In order to solve decision-making problems with flexible operational parameter under neutrosophic cubic environments, the paper extends the Dombi operations to neutrosophic cubic sets and proposes a neutrosophic cubic Dombi weighted arithmetic average (NCDWAA) operator and a neutrosophic cubic Dombi weighted geometric average (NCDWGA) operator. Then, we propose a multiple attribute decision-making (MADM) method based on the NCDWAA and NCDWGA operators. Finally, we provide two illustrative examples of MADM to demonstrate the application and effectiveness of the established method. Full article
Open AccessArticle Modified Cuckoo Search Algorithm with Variational Parameters and Logistic Map
Algorithms 2018, 11(3), 30; doi:10.3390/a11030030
Received: 17 January 2018 / Revised: 6 March 2018 / Accepted: 14 March 2018 / Published: 15 March 2018
PDF Full-text (848 KB) | HTML Full-text | XML Full-text
Abstract
Cuckoo Search (CS) is a Meta-heuristic method, which exhibits several advantages such as easier to application and fewer tuning parameters. However, it has proven to very easily fall into local optimal solutions and has a slow rate of convergence. Therefore, we propose Modified
[...] Read more.
Cuckoo Search (CS) is a Meta-heuristic method, which exhibits several advantages such as easier to application and fewer tuning parameters. However, it has proven to very easily fall into local optimal solutions and has a slow rate of convergence. Therefore, we propose Modified cuckoo search algorithm with variational parameter and logistic map (VLCS) to ameliorate these defects. To balance the exploitation and exploration of the VLCS algorithm, we not only use the coefficient function to change step size α and probability of detection p a at next generation, but also use logistic map of each dimension to initialize host nest location and update the location of host nest beyond the boundary. With fifteen benchmark functions, the simulations demonstrate that the VLCS algorithm can over come the disadvantages of the CS algorithm.In addition, the VLCS algorithm is good at dealing with high dimension problems and low dimension problems. Full article
(This article belongs to the Special Issue Evolutionary Computation for Multiobjective Optimization)
Figures

Figure 1

Open AccessArticle Bilayer Local Search Enhanced Particle Swarm Optimization for the Capacitated Vehicle Routing Problem
Algorithms 2018, 11(3), 31; doi:10.3390/a11030031
Received: 29 January 2018 / Revised: 7 March 2018 / Accepted: 13 March 2018 / Published: 15 March 2018
Cited by 1 | PDF Full-text (2374 KB) | HTML Full-text | XML Full-text
Abstract
The classical capacitated vehicle routing problem (CVRP) is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions
[...] Read more.
The classical capacitated vehicle routing problem (CVRP) is a very popular combinatorial optimization problem in the field of logistics and supply chain management. Although CVRP has drawn interests of many researchers, no standard way has been established yet to obtain best known solutions for all the different problem sets. We propose an efficient algorithm Bilayer Local Search-based Particle Swarm Optimization (BLS-PSO) along with a novel decoding method to solve CVRP. Decoding method is important to relate the encoded particle position to a feasible CVRP solution. In bilayer local search, one layer of local search is for the whole population in any iteration whereas another one is applied only on the pool of the best particles generated in different generations. Such searching strategies help the BLS-PSO to perform better than the existing proposals by obtaining best known solutions for most of the existing benchmark problems within very reasonable computational time. Computational results also show that the performance achieved by the proposed algorithm outperforms other PSO-based approaches. Full article
(This article belongs to the Special Issue Metaheuristics for Rich Vehicle Routing Problems)
Figures

Figure 1

Open AccessArticle Inverse Properties in Neutrosophic Triplet Loop and Their Application to Cryptography
Algorithms 2018, 11(3), 32; doi:10.3390/a11030032
Received: 7 February 2018 / Revised: 11 March 2018 / Accepted: 12 March 2018 / Published: 16 March 2018
PDF Full-text (298 KB) | HTML Full-text | XML Full-text
Abstract
This paper is the first study of the neutrosophic triplet loop (NTL) which was originally introduced by Floretin Smarandache. NTL originated from the neutrosophic triplet set X: a collection of triplets (x,neut(x),
[...] Read more.
This paper is the first study of the neutrosophic triplet loop (NTL) which was originally introduced by Floretin Smarandache. NTL originated from the neutrosophic triplet set X: a collection of triplets ( x , n e u t ( x ) , a n t i ( x ) ) for an x X which obeys some axioms (existence of neutral(s) and opposite(s)). NTL can be informally said to be a neutrosophic triplet group that is not associative. That is, a neutrosophic triplet group is an NTL that is associative. In this study, NTL with inverse properties such as: right inverse property (RIP), left inverse property (LIP), right cross inverse property (RCIP), left cross inverse property (LCIP), right weak inverse property (RWIP), left weak inverse property (LWIP), automorphic inverse property (AIP), and anti-automorphic inverse property are introduced and studied. The research was carried out with the following assumptions: the inverse property (IP) is the RIP and LIP, cross inverse property (CIP) is the RCIP and LCIP, weak inverse property (WIP) is the RWIP and LWIP. The algebraic properties of neutrality and opposite in the aforementioned inverse property NTLs were investigated, and they were found to share some properties with the neutrosophic triplet group. The following were established: (1) In a CIPNTL (IPNTL), RIP (RCIP) and LIP (LCIP) were equivalent; (2) In an RIPNTL (LIPNTL), the CIP was equivalent to commutativity; (3) In a commutative NTL, the RIP, LIP, RCIP, and LCIP were found to be equivalent; (4) In an NTL, IP implied anti-automorphic inverse property and WIP, RCIP implied AIP and RWIP, while LCIP implied AIP and LWIP; (5) An NTL has the IP (CIP) if and only if it has the WIP and anti-automorphic inverse property (AIP); (6) A CIPNTL or an IPNTL was a quasigroup; (7) An LWIPNTL (RWIPNTL) was a left (right) quasigroup. The algebraic behaviours of an element, its neutral and opposite in the associator and commutator of a CIPNTL or an IPNTL were investigated. It was shown that ( Z p , ) where x y = ( p 1 ) ( x + y ) , for any prime p, is a non-associative commutative CIPNTL and IPNTL. The application of some of these varieties of inverse property NTLs to cryptography is discussed. Full article
Figures

Figure 1

Open AccessArticle An Online Energy Management Control for Hybrid Electric Vehicles Based on Neuro-Dynamic Programming
Algorithms 2018, 11(3), 33; doi:10.3390/a11030033
Received: 9 February 2018 / Revised: 11 March 2018 / Accepted: 13 March 2018 / Published: 19 March 2018
PDF Full-text (1778 KB) | HTML Full-text | XML Full-text
Abstract
Hybrid electric vehicles are a compromise between traditional vehicles and pure electric vehicles and can be part of the solution to the energy shortage problem. Energy management strategies (EMSs) are highly related to energy utilization in HEVs’ fuel economy. In this research, we
[...] Read more.
Hybrid electric vehicles are a compromise between traditional vehicles and pure electric vehicles and can be part of the solution to the energy shortage problem. Energy management strategies (EMSs) are highly related to energy utilization in HEVs’ fuel economy. In this research, we have employed a neuro-dynamic programming (NDP) method to simultaneously optimize fuel economy and battery state of charge (SOC). In this NDP method, the critic network is a multi-resolution wavelet neural network based on the Meyer wavelet function, and the action network is a conventional wavelet neural network based on the Morlet function. The weights and parameters of both networks are obtained by an algorithm of backpropagation type. The NDP-based EMS has been applied to a parallel HEV and compared with a previously reported NDP EMS and a stochastic dynamic programing-based method. Simulation results under ADVISOR2002 have shown that the proposed NDP approach achieves better performance than both the methods. These indicate that the proposed NDP EMS, and the CWNN and MRWNN, are effective in approximating a nonlinear system. Full article
(This article belongs to the Special Issue Advanced Artificial Neural Networks)
Figures

Figure 1

Back to Top