Search results for: Kruskal algorithm
3681 Text Based Shuffling Algorithm on Graphics Processing Unit for Digital Watermarking
Authors: Zayar Phyo, Ei Chaw Htoon
Abstract:
In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel
Procedia PDF Downloads 1523680 An Algorithm for the Map Labeling Problem with Two Kinds of Priorities
Authors: Noboru Abe, Yoshinori Amai, Toshinori Nakatake, Sumio Masuda, Kazuaki Yamaguchi
Abstract:
We consider the problem of placing labels of the points on a plane. For each point, its position, the size of its label and a priority are given. Moreover, several candidates of its label positions are prespecified, and each of such label positions is assigned a priority. The objective of our problem is to maximize the total sum of priorities of placed labels and their points. By refining a labeling algorithm that can use these priorities, we propose a new heuristic algorithm which is more suitable for treating the assigned priorities.Keywords: map labeling, greedy algorithm, heuristic algorithm, priority
Procedia PDF Downloads 4343679 The Tendon Reflexes on the Performance of Flanker Task in the Subjects of Cerebrovascular Accidents
Authors: Harshdeep Singh, Kuljeet Singh Anand
Abstract:
Background: Cerebrovascular Accidents (CVA) cause abnormal or asymmetrical tendon reflexes contributing to motor impairments. Since the tendon reflexes are mediated by the spinal cord, their effects on cognitive performances are overlooked. This study aims to find the contributions of tendon reflexes on the performance of the Flanker task. Methods: A total population of 46 mixed subjects with movement disorders were recruited for the study. Deep tendon reflexes (DTR) of the biceps, triceps and brachioradialis were assessed for both upper extremities. Later, the Flanker task was performed on all the subjects, and the mean Reaction Time (RT) along with both the congruent and incongruent stimuli were evaluated. For the final analysis, the Kruskal Wallis test was performed to see the difference between the DTR and the performance of the Flanker Task. Results: The Kruskal Wallis test results showed a significant difference between the DTR scores, X²(2) = 11.328, p= 0.023 with the mean RT of the flanker task and X²(2) = 9.531, p= 0.049 with mean RT of the Incongruent Stimuli. Whereas the result found a non-significant difference in the mean RT of the Congruent Stimuli. Conclusion: Each DTR score is distributed differently with the mean RT of the flanker task and for the incongruent stimuli as well. Therefore, the tendon reflexes in PD may be contributing to the performance of the Flanker Task and may be an indicator of abnormal cognitive performance. Further research is needed to evaluate how the RTs are distributed with each DTR score.Keywords: cerebrovascular accidents, deep tendon reflexes, flanker task, reaction time, congruent stimuli, incongruent stimuli
Procedia PDF Downloads 1043678 Examining How Teachers’ Backgrounds and Perceptions for Technology Use Influence on Students’ Achievements
Authors: Zhidong Zhang, Amanda Resendez
Abstract:
This study is to examine how teachers’ perspective on education technology use in their class influence their students’ achievement. The authors hypothesized that teachers’ perspective can directly or indirectly influence students’ learning, performance, and achievements. In this study, a questionnaire entitled, Teacher’s Perspective on Educational Technology, was delivered to 63 teachers and 1268 students’ mathematics and reading achievement records were collected. The questionnaire consists of four parts: a) demographic variables, b) attitudes on technology integration, c) outside factor affecting technology integration, and d) technology use in the classroom. Kruskal-Wallis and hierarchical regression analysis techniques were used to examine: 1) the relationship between the demographic variables and teachers’ perspectives on educational technology, and 2) how the demographic variables were causally related to students’ mathematics and reading achievements. The study found that teacher demographics were significantly related to the teachers’ perspective on educational technology with p < 0.05 and p < 0.01 separately. These teacher demographical variables included the school district, age, gender, the grade currently teach, teaching experience, and proficiency using new technology. Further, these variables significantly predicted students’ mathematics and reading achievements with p < 0.05 and p < 0.01 separately. The variations of R² are between 0.176 and 0.467. That means 46.7% of the variance of a given analysis can be explained by the model.Keywords: teacher's perception of technology use, mathematics achievement, reading achievement, Kruskal-Wallis test, hierarchical regression analysis
Procedia PDF Downloads 1333677 A Hybrid Distributed Algorithm for Multi-Objective Dynamic Flexible Job Shop Scheduling Problem
Authors: Aydin Teymourifar, Gurkan Ozturk
Abstract:
In this paper, a hybrid distributed algorithm has been suggested for multi-objective dynamic flexible job shop scheduling problem. The proposed algorithm is high level, in which several algorithms search the space on different machines simultaneously also it is a hybrid algorithm that takes advantages of the artificial intelligence, evolutionary and optimization methods. Distribution is done at different levels and new approaches are used for design of the algorithm. Apache spark and Hadoop frameworks have been used for the distribution of the algorithm. The Pareto optimality approach is used for solving the multi-objective benchmarks. The suggested algorithm that is able to solve large-size problems in short times has been compared with the successful algorithms of the literature. The results prove high speed and efficiency of the algorithm.Keywords: distributed algorithms, apache-spark, Hadoop, flexible dynamic job shop scheduling, multi-objective optimization
Procedia PDF Downloads 3543676 A Variant of a Double Structure-Preserving QR Algorithm for Symmetric and Hamiltonian Matrices
Authors: Ahmed Salam, Haithem Benkahla
Abstract:
Recently, an efficient backward-stable algorithm for computing eigenvalues and vectors of a symmetric and Hamiltonian matrix has been proposed. The method preserves the symmetric and Hamiltonian structures of the original matrix, during the whole process. In this paper, we revisit the method. We derive a way for implementing the reduction of the matrix to the appropriate condensed form. Then, we construct a novel version of the implicit QR-algorithm for computing the eigenvalues and vectors.Keywords: block implicit QR algorithm, preservation of a double structure, QR algorithm, symmetric and Hamiltonian structures
Procedia PDF Downloads 4093675 A New Tool for Global Optimization Problems: Cuttlefish Algorithm
Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman
Abstract:
This paper presents a new meta-heuristic bio-inspired optimization algorithm which is called Cuttlefish Algorithm (CFA). The algorithm mimics the mechanism of color changing behavior of the cuttlefish to solve numerical global optimization problems. The colors and patterns of the cuttlefish are produced by reflected light from three different layers of cells. The proposed algorithm considers mainly two processes: reflection and visibility. Reflection process simulates light reflection mechanism used by these layers, while visibility process simulates visibility of matching patterns of the cuttlefish. To show the effectiveness of the algorithm, it is tested with some other popular bio-inspired optimization algorithms such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Bees Algorithm (BA) that have been previously proposed in the literature. Simulations and obtained results indicate that the proposed CFA is superior when compared with these algorithms.Keywords: Cuttlefish Algorithm, bio-inspired algorithms, optimization, global optimization problems
Procedia PDF Downloads 5663674 Using Genetic Algorithms and Rough Set Based Fuzzy K-Modes to Improve Centroid Model Clustering Performance on Categorical Data
Authors: Rishabh Srivastav, Divyam Sharma
Abstract:
We propose an algorithm to cluster categorical data named as ‘Genetic algorithm initialized rough set based fuzzy K-Modes for categorical data’. We propose an amalgamation of the simple K-modes algorithm, the Rough and Fuzzy set based K-modes and the Genetic Algorithm to form a new algorithm,which we hypothesise, will provide better Centroid Model clustering results, than existing standard algorithms. In the proposed algorithm, the initialization and updation of modes is done by the use of genetic algorithms while the membership values are calculated using the rough set and fuzzy logic.Keywords: categorical data, fuzzy logic, genetic algorithm, K modes clustering, rough sets
Procedia PDF Downloads 2503673 An Improved Ant Colony Algorithm for Genome Rearrangements
Authors: Essam Al Daoud
Abstract:
Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort
Procedia PDF Downloads 3453672 Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network
Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi
Abstract:
In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks
Procedia PDF Downloads 4043671 The Effect of Aromatherapy Candle as Insecticide from Citrus Extract of Lemongrass (Cymbopogon) to Increase Ae. aegypti Mortality
Authors: Nurul Hidayah, Farida Rahmatika, Fathimah Azzahra, Nesty Herennadia
Abstract:
Aromatherapy candles are one of the insecticide media that have not been much researched. The active ingredient that is proven to have the effect of insecticide is a citrus extract from lemongrass oil (Cymbopogon). Aromatherapy candles are added by citrus compounds to be insecticidal for Ae. aegypti mosquito that was related to the infectious disease such as dengue fever. This research aims to find out if aromatherapy candles of citrus compounds have an insecticidal effect on Ae. aegypti mosquito. We used true experimental design including posttest only with control group design. The samples are 20 male and female Ae. aegypti mosquitos with aged 1-7 days belong to the inclusion criteria. The subjects were divided into 6 groups, consisting of 1 negative control group and 5 treatment groups with variation concentration are 1%; 2%; 3%; 4%; 5%. Each group will be treated for 2 hours and observed death after 24 hours. Replication in each group is done 4 times. The results were then tested statistically using Kruskal-Wallis and probit test. Mean of death in negative control group, and treatment group 1%; 2%; 3%; 4%; 5% respectively 0; 1; 0.25; 0; 1 and 1 mosquito. The Kruskal-Wallis test in the study group found no significant difference (p = 0.178). The probit analysis showed that LC50 and LC90 were 20.069% and 31.557%. The aromatherapy candle of a citrus compound has an insecticidal effect on the Ae aegypti mosquito.Keywords: Ae. aegypti insecticide, aromatherapy candle, citrus compound, lemongrass oil (Cymbopogon)
Procedia PDF Downloads 1913670 A Fast Silhouette Detection Algorithm for Shadow Volumes in Augmented Reality
Authors: Hoshang Kolivand, Mahyar Kolivand, Mohd Shahrizal Sunar, Mohd Azhar M. Arsad
Abstract:
Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments.Keywords: silhouette detection, shadow volumes, real-time shadows, rendering, augmented reality
Procedia PDF Downloads 4433669 An Enhanced Harmony Search (ENHS) Algorithm for Solving Optimization Problems
Authors: Talha A. Taj, Talha A. Khan, M. Imran Khalid
Abstract:
Optimization techniques attract researchers to formulate a problem and determine its optimum solution. This paper presents an Enhanced Harmony Search (ENHS) algorithm for solving optimization problems. The proposed algorithm increases the convergence and is more efficient than the standard Harmony Search (HS) algorithm. The paper discusses the novel techniques in detail and also provides the strategy for tuning the decisive parameters that affects the efficiency of the ENHS algorithm. The algorithm is tested on various benchmark functions, a real world optimization problem and a constrained objective function. Also, the results of ENHS are compared to standard HS, and various other optimization algorithms. The ENHS algorithms prove to be significantly better and more efficient than other algorithms. The simulation and testing of the algorithms is performed in MATLAB.Keywords: optimization, harmony search algorithm, MATLAB, electronic
Procedia PDF Downloads 4643668 A Novel Algorithm for Production Scheduling
Authors: Ali Mohammadi Bolban Abad, Fariborz Ahmadi
Abstract:
Optimization in manufacture is a method to use limited resources to obtain the best performance and reduce waste. In this paper a new algorithm based on eurygaster life is introduced to obtain a plane in which task order and completion time of resources are defined. Evaluation results show our approach has less make span when the resources are allocated with some products in comparison to genetic algorithm.Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, NP-Hard problems, production scheduling
Procedia PDF Downloads 3803667 Downscaling Daily Temperature with Neuroevolutionary Algorithm
Authors: Min Shi
Abstract:
State of the art research with Artificial Neural Networks for the downscaling of General Circulation Models (GCMs) mainly uses back-propagation algorithm as a training approach. This paper introduces another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.Keywords: temperature, downscaling, artificial neural networks, evolutionary algorithms
Procedia PDF Downloads 3523666 An Optimization Algorithm Based on Dynamic Schema with Dissimilarities and Similarities of Chromosomes
Authors: Radhwan Yousif Sedik Al-Jawadi
Abstract:
Optimization is necessary for finding appropriate solutions to a range of real-life problems. In particular, genetic (or more generally, evolutionary) algorithms have proved very useful in solving many problems for which analytical solutions are not available. In this paper, we present an optimization algorithm called Dynamic Schema with Dissimilarity and Similarity of Chromosomes (DSDSC) which is a variant of the classical genetic algorithm. This approach constructs new chromosomes from a schema and pairs of existing ones by exploring their dissimilarities and similarities. To show the effectiveness of the algorithm, it is tested and compared with the classical GA, on 15 two-dimensional optimization problems taken from literature. We have found that, in most cases, our method is better than the classical genetic algorithm.Keywords: chromosome injection, dynamic schema, genetic algorithm, similarity and dissimilarity
Procedia PDF Downloads 3493665 Simulation Approach for a Comparison of Linked Cluster Algorithm and Clusterhead Size Algorithm in Ad Hoc Networks
Authors: Ameen Jameel Alawneh
Abstract:
A Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts that dynamically form a temporary network without the aid of a system administrator. It has neither fixed infrastructure nor wireless ad hoc sessions. It inherently reaches several nodes with a single transmission, and each node functions as both a host and a router. The network maybe represented as a set of clusters each managed by clusterhead. The cluster size is not fixed and it depends on the movement of nodes. We proposed a clusterhead size algorithm (CHSize). This clustering algorithm can be used by several routing algorithms for ad hoc networks. An elected clusterhead is assigned for communication with all other clusters. Analysis and simulation of the algorithm has been implemented using GloMoSim networks simulator, MATLAB and MAPL11 proved that the proposed algorithm achieves the goals.Keywords: simulation, MANET, Ad-hoc, cluster head size, linked cluster algorithm, loss and dropped packets
Procedia PDF Downloads 3963664 Hybrid Algorithm for Frequency Channel Selection in Wi-Fi Networks
Authors: Cesar Hernández, Diego Giral, Ingrid Páez
Abstract:
This article proposes a hybrid algorithm for spectrum allocation in cognitive radio networks based on the algorithms Analytical Hierarchical Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to improve the performance of the spectrum mobility of secondary users in cognitive radio networks. To calculate the level of performance of the proposed algorithm a comparative analysis between the proposed AHP-TOPSIS, Grey Relational Analysis (GRA) and Multiplicative Exponent Weighting (MEW) algorithm is performed. Four evaluation metrics is used. These metrics are the accumulative average of failed handoffs, the accumulative average of handoffs performed, the accumulative average of transmission bandwidth, and the accumulative average of the transmission delay. The results of the comparison show that AHP-TOPSIS Algorithm provides 2.4 times better performance compared to a GRA Algorithm and, 1.5 times better than the MEW Algorithm.Keywords: cognitive radio, decision making, hybrid algorithm, spectrum handoff, wireless networks
Procedia PDF Downloads 5423663 Modified Active (MA) Algorithm to Generate Semantic Web Related Clustered Hierarchy for Keyword Search
Authors: G. Leena Giri, Archana Mathur, S. H. Manjula, K. R. Venugopal, L. M. Patnaik
Abstract:
Keyword search in XML documents is based on the notion of lowest common ancestors in the labelled trees model of XML documents and has recently gained a lot of research interest in the database community. In this paper, we propose the Modified Active (MA) algorithm which is an improvement over the active clustering algorithm by taking into consideration the entity aspect of the nodes to find the level of the node pertaining to a particular keyword input by the user. A portion of the bibliography database is used to experimentally evaluate the modified active algorithm and results show that it performs better than the active algorithm. Our modification improves the response time of the system and thereby increases the efficiency of the system.Keywords: keyword matching patterns, MA algorithm, semantic search, knowledge management
Procedia PDF Downloads 4153662 Cuckoo Search (CS) Optimization Algorithm for Solving Constrained Optimization
Authors: Sait Ali Uymaz, Gülay Tezel
Abstract:
This paper presents the comparison results on the performance of the Cuckoo Search (CS) algorithm for constrained optimization problems. For constraint handling, CS algorithm uses penalty method. CS algorithm is tested on thirteen well-known test problems and the results obtained are compared to Particle Swarm Optimization (PSO) algorithm. Mean, best, median and worst values were employed for the analyses of performance.Keywords: cuckoo search, particle swarm optimization, constrained optimization problems, penalty method
Procedia PDF Downloads 5593661 Left to Right-Right Most Parsing Algorithm with Lookahead
Authors: Jamil Ahmed
Abstract:
Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm
Procedia PDF Downloads 1263660 Improved Whale Algorithm Based on Information Entropy and Its Application in Truss Structure Optimization Design
Authors: Serges Mendomo Meye, Li Guowei, Shen Zhenzhong, Gan Lei, Xu Liqun
Abstract:
Given the limitations of the original whale optimization algorithm (WAO) in local optimum and low convergence accuracy in truss structure optimization problems, based on the fundamental whale algorithm, an improved whale optimization algorithm (SWAO) based on information entropy is proposed. The information entropy itself is an uncertain measure. It is used to control the range of whale searches in path selection. It can overcome the shortcomings of the basic whale optimization algorithm (WAO) and can improve the global convergence speed of the algorithm. Taking truss structure as the optimization research object, the mathematical model of truss structure optimization is established; the cross-sectional area of truss is taken as the design variable; the objective function is the weight of truss structure; and an improved whale optimization algorithm (SWAO) is used for optimization design, which provides a new idea and means for its application in large and complex engineering structure optimization design.Keywords: information entropy, structural optimization, truss structure, whale algorithm
Procedia PDF Downloads 2503659 Parallel Version of Reinhard’s Color Transfer Algorithm
Authors: Abhishek Bhardwaj, Manish Kumar Bajpai
Abstract:
An image with its content and schema of colors presents an effective mode of information sharing and processing. By changing its color schema different visions and prospect are discovered by the users. This phenomenon of color transfer is being used by Social media and other channel of entertainment. Reinhard et al’s algorithm was the first one to solve this problem of color transfer. In this paper, we make this algorithm efficient by introducing domain parallelism among different processors. We also comment on the factors that affect the speedup of this problem. In the end by analyzing the experimental data we claim to propose a novel and efficient parallel Reinhard’s algorithm.Keywords: Reinhard et al’s algorithm, color transferring, parallelism, speedup
Procedia PDF Downloads 6143658 A Filtering Algorithm for a Nonlinear State-Space Model
Authors: Abdullah Eqal Al Mazrooei
Abstract:
Kalman filter is a famous algorithm that utilizes to estimate the state in the linear systems. It has numerous applications in technology and science. Since of the most of applications in real life can be described by nonlinear systems. So, Kalman filter does not work with the nonlinear systems because it is suitable to linear systems only. In this work, a nonlinear filtering algorithm is presented which is suitable to use with the special kinds of nonlinear systems. This filter generalizes the Kalman filter. This means that this filter also can be used for the linear systems. Our algorithm depends on a special linearization of the second degree. We introduced the nonlinear algorithm with a bilinear state-space model. A simulation example is presented to illustrate the efficiency of the algorithm.Keywords: Kalman filter, filtering algorithm, nonlinear systems, state-space model
Procedia PDF Downloads 3773657 Chemical Reaction Algorithm for Expectation Maximization Clustering
Authors: Li Ni, Pen ManMan, Li KenLi
Abstract:
Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering
Procedia PDF Downloads 7153656 An Improved Genetic Algorithm for Traveling Salesman Problem with Precedence Constraint
Authors: M. F. F. Ab Rashid, A. N. Mohd Rose, N. M. Z. Nik Mohamed, W. S. Wan Harun, S. A. Che Ghani
Abstract:
Traveling salesman problem with precedence constraint (TSPPC) is one of the most complex problems in combinatorial optimization. The existing algorithms to solve TSPPC cost large computational time to find the optimal solution. The purpose of this paper is to present an efficient genetic algorithm that guarantees optimal solution with less number of generations and iterations time. Unlike the existing algorithm that generates priority factor as chromosome, the proposed algorithm directly generates sequence of solution as chromosome. As a result, the proposed algorithm is capable of generating optimal solution with smaller number of generations and iteration time compare to existing algorithm.Keywords: traveling salesman problem, sequencing, genetic algorithm, precedence constraint
Procedia PDF Downloads 5613655 Improved FP-Growth Algorithm with Multiple Minimum Supports Using Maximum Constraints
Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam
Abstract:
Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FP-growth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.Keywords: association rules, FP-growth, multiple minimum supports, Weka tool
Procedia PDF Downloads 4873654 An Improved Many Worlds Quantum Genetic Algorithm
Authors: Li Dan, Zhao Junsuo, Zhang Wenjun
Abstract:
Aiming at the shortcomings of the Quantum Genetic Algorithm such as the multimodal function optimization problems easily falling into the local optimum, and vulnerable to premature convergence due to no closely relationship between individuals, the paper presents an Improved Many Worlds Quantum Genetic Algorithm (IMWQGA). The paper using the concept of Many Worlds; using the derivative way of parallel worlds’ parallel evolution; putting forward the thought which updating the population according to the main body; adopting the transition methods such as parallel transition, backtracking, travel forth. In addition, the algorithm in the paper also proposes the quantum training operator and the combinatorial optimization operator as new operators of quantum genetic algorithm.Keywords: quantum genetic algorithm, many worlds, quantum training operator, combinatorial optimization operator
Procedia PDF Downloads 7453653 Multi-Subpopulation Genetic Algorithm with Estimation of Distribution Algorithm for Textile Batch Dyeing Scheduling Problem
Authors: Nhat-To Huynh, Chen-Fu Chien
Abstract:
Textile batch dyeing scheduling problem is complicated which includes batch formation, batch assignment on machines, batch sequencing with sequence-dependent setup time. Most manufacturers schedule their orders manually that are time consuming and inefficient. More power methods are needed to improve the solution. Motivated by the real needs, this study aims to propose approaches in which genetic algorithm is developed with multi-subpopulation and hybridised with estimation of distribution algorithm to solve the constructed problem for minimising the makespan. A heuristic algorithm is designed and embedded into the proposed algorithms to improve the ability to get out of the local optima. In addition, an empirical study is conducted in a textile company in Taiwan to validate the proposed approaches. The results have showed that proposed approaches are more efficient than simulated annealing algorithm.Keywords: estimation of distribution algorithm, genetic algorithm, multi-subpopulation, scheduling, textile dyeing
Procedia PDF Downloads 3003652 A Rapid Code Acquisition Scheme in OOC-Based CDMA Systems
Authors: Keunhong Chae, Seokho Yoon
Abstract:
We propose a code acquisition scheme called improved multiple-shift (IMS) for optical code division multiple access systems, where the optical orthogonal code is used instead of the pseudo noise code. Although the IMS algorithm has a similar process to that of the conventional MS algorithm, it has a better code acquisition performance than the conventional MS algorithm. We analyze the code acquisition performance of the IMS algorithm and compare the code acquisition performances of the MS and the IMS algorithms in single-user and multi-user environments.Keywords: code acquisition, optical CDMA, optical orthogonal code, serial algorithm
Procedia PDF Downloads 540