Abstract: Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.
Abstract: Today, the need for water sources is swiftly increasing due to population growth. At the same time, it is known that some regions will face with shortage of water and drought because of the global warming and climate change. In this context, evaluation and analysis of hydrological data such as the observed trends, drought and flood prediction of short term flow has great deal of importance. The most accurate selection probability distribution is important to describe the low flow statistics for the studies related to drought analysis. As in many basins In Turkey, Gediz River basin will be affected enough by the drought and will decrease the amount of used water. The aim of this study is to derive appropriate probability distributions for frequency analysis of annual minimum flows at 6 gauging stations of the Gediz Basin. After applying 10 different probability distributions, six different parameter estimation methods and 3 fitness test, the Pearson 3 distribution and general extreme values distributions were found to give optimal results.
Abstract: The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.
Abstract: Leather industry is the most important traditional
industry to provide the leather products in the world for thousand
years. The fierce global competitive environment and common
awareness of global carbon reduction make livestock supply quantities
falling, salt and wet blue leather material reduces and the price
skyrockets significantly. Exchange rate fluctuation led sales revenue
decreasing which due to the differences of export exchanges and
compresses the overall profitability of leather industry. This paper
applies activity-based benefit assessment approach to build up fitness
fur input mixed model, fur is Wet Blue, which concerned with four key
factors: the output rate of wet blue, unit cost of wet blue, yield rate and
grade level of Wet Blue to achieve the low cost strategy under given
unit price of leather product condition of the company. The research
findings indicate that applying this model may improve the input cost
structure, decrease numbers of leather product inventories and to raise
the competitive advantages of the enterprise in the future.
Abstract: The present work deals with the optimal placement of piezoelectric actuators on a thin plate using Modified Control Matrix and Singular Value Decomposition (MCSVD) approach. The problem has been formulated using the finite element method using ten piezoelectric actuators on simply supported plate to suppress first six modes. The sizes of ten actuators are combined to outline one actuator by adding the ten columns of control matrix to form a column matrix. The singular value of column control matrix is considered as the fitness function and optimal positions of the actuators are obtained by maximizing it with GA. Vibration suppression has been studied for simply supported plate with piezoelectric patches in optimal positions using Linear Quadratic regulator) scheme. It is observed that MCSVD approach has given the position of patches adjacent to each-other, symmetric to the centre axis and given greater vibration suppression than other previously published results on SVD.
Abstract: The aim of this study was to describe typical changes in several parameters of body composition – the amount of skeletal muscle mass (SMM), % body fat (BF) and body mass index (BMI) - in selected age categories (30+ years) of men and women in the Czech Republic, depending on the degree of sports activity. Study (n = 823, M = 343, F = 480) monitored differences in BF, SM and BMI in five age groups (from 30-39 years to 70+ years). Physically inactive individuals have (p < 0.05) higher % BF in comparison with physically active individuals (29.5 ± 0.59 vs. 27 ± 0.38%), higher BMI (27.3 ± 0.32 vs. 26.1 ± 0.20 kg/m2), but lower SM (39.0 ± 0.33 vs. 40.4 ± 0.21%). The results indicate that with an increasing age, there is a trend towards increasing values of BMI and % BF, and decreasing values of SMM.
Abstract: A numerical simulation of optimization all of electrospinning processing parameters to obtain smallest nanofiber diameter have been performed by employing genetic algorithm (GA). Fitness function in genetic algorithm methods, which was different for each parameter, was determined by simulation approach based on the Reneker’s model. Moreover, others genetic algorithm parameter, namely length of population, crossover and mutation were applied to get the optimum electrospinning processing parameters. In addition, minimum fiber diameter, 32 nm, was achieved from a simulation by applied the optimum parameters of electrospinning. This finding may be useful for process control and prediction of electrospun fiber production. In this paper, it is also compared between predicted parameters with some experimental results.
Abstract: This paper discusses the use of a computerized test to measure the decision-making abilities of teenage basketball players in Singapore. There are five sections in this test – Competitive state anxiety inventory-2 (CSAI-2) questionnaire (measures player’s cognitive anxiety, somatic anxiety and self-confidence), Corsi block-tapping task (measures player’s short-term spatial memory), situation awareness global assessment technique (SAGAT) (measures players’ situation awareness in a basketball game), multiple choice questions on basketball knowledge (measures players’ knowledge of basketball rules and concepts), and lastly, a learning test that requires participants to recall and recognize basketball set plays (measures player’s ability to learn and recognize set plays). A total of 25 basketball players, aged 14 to 16 years old, from three secondary school teams participated in this experiment. The results that these basketball players obtained from this cognitive test were then used to compare with their physical fitness and basketball performance.
Abstract: In this paper a genetic algorithm (GA) with dual-fitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machine scheduling using simulated data. The results obtained from the proposed GA were compared with classical GA and integer programming (IP). Results showed that dual-fitness function GA outperformed the classical single-fitness function GA with statistical significance for large problems and was competitive to IP, particularly when large size problems were used.
Abstract: The DNA microarray technology concurrently monitors the expression levels of thousands of genes during significant biological processes and across the related samples. The better understanding of functional genomics is obtained by extracting the patterns hidden in gene expression data. It is handled by clustering which reveals natural structures and identify interesting patterns in the underlying data. In the proposed work clustering gene expression data is done through an Advanced Nelder Mead (ANM) algorithm. Nelder Mead (NM) method is a method designed for optimization process. In Nelder Mead method, the vertices of a triangle are considered as the solutions. Many operations are performed on this triangle to obtain a better result. In the proposed work, the operations like reflection and expansion is eliminated and a new operation called spread-out is introduced. The spread-out operation will increase the global search area and thus provides a better result on optimization. The spread-out operation will give three points and the best among these three points will be used to replace the worst point. The experiment results are analyzed with optimization benchmark test functions and gene expression benchmark datasets. The results show that ANM outperforms NM in both benchmarks.
Abstract: In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.
Abstract: In this paper the authors present the framework of a
system for assisting users through counseling on personal health, the
Personal Health Assistance Service Expert System (PHASES).
Personal health assistance systems need Personal Health Records
(PHR), which support wellness activities, improve the understanding
of personal health issues, enable access to data from providers of
health services, strengthen health promotion, and in the end improve
the health of the population. This is especially important in societies
where the health costs increase at a higher rate than the overall
economy. The most important elements of a healthy lifestyle are
related to food (such as balanced nutrition and diets), activities for
body fitness (such as walking, sports, fitness programs), and other
medical treatments (such as massage, prescriptions of drugs). The
PHASES framework uses an ontology of food, which includes
nutritional facts, an expert system keeping track of personal health
data that are matched with medical treatments, and a comprehensive
data transfer between patients and the system.
Abstract: Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.
Abstract: In this paper we present a GP-based method for automatically evolve projections, so that data can be more easily classified in the projected spaces. At the same time, our approach can reduce dimensionality by constructing more relevant attributes. Fitness of each projection measures how easy is to classify the dataset after applying the projection. This is quickly computed by a Simple Linear Perceptron. We have tested our approach in three domains. The experiments show that it obtains good results, compared to other Machine Learning approaches, while reducing dimensionality in many cases.
Abstract: The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.
Abstract: Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.
Abstract: Several researchers have proposed methods about
combination of Genetic Algorithm (GA) and Fuzzy Logic (the use of
GA to obtain fuzzy rules and application of fuzzy logic in
optimization of GA). In this paper, we suggest a new method in
which fuzzy decision making is used to improve the performance of
genetic algorithm. In the suggested method, we determine the alleles
that enhance the fitness of chromosomes and try to insert them to the
next generation.
In this algorithm we try to present an innovative vaccination in the
process of reproduction in genetic algorithm, with considering the
trade off between exploration and exploitation.
Abstract: The hybridization of artificial immune system with
cellular automata (CA-AIS) is a novel method. In this hybrid model,
the cellular automaton within each cell deploys the artificial immune
system algorithm under optimization context in order to increase its
fitness by using its neighbor-s efforts. The hybrid model CA-AIS is
introduced to fix the standard artificial immune system-s weaknesses.
The credibility of the proposed approach is evaluated by simulations
and it shows that the proposed approach achieves better results
compared to standard artificial immune system.
Abstract: In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.
Abstract: Whilst there is growing evidence that activity across
the lifespan is beneficial for improved health, there are also many
changes involved with the aging process and subsequently the
potential for reduced indices of health. The nexus between all forms
of health, physical activity and aging is complex and has raised much
interest in recent times due to the realization that a multifaceted
approached is necessary in order to counteract a growing obesity
epidemic. By investigating age based trends within a population
adherring to competitive sport at older ages, further insight might be
gleaned to assist in understanding one of many factors influencing
this relationship. This study evaluated those sport psychological
constructs of health, physical fitness, mental health states, and social
dimension factors in sport that were associated with factors to
participate in sport and physical activity based on responses from the
2009 World Masters Games in Sydney. The sample consisted of
7846 athletes who competed at the games and who completed a 56
item sports participation survey using a 7-point Likert response (1 -
not important to 7 - very important). Questions focuses on factors
thought to promote participation, such as weight control, living
longer, improving mental health (self-esteem, mood states),
improving physical health and factors related to the athlete-s
competitive perspective. The most significant factors related to
participation with this cohort of masters athletes were the socializing
environment of sport, getting physically fit and improving
competitive personal best performances. Strategies to increase
participation in masters sport should focus on these factors as other
factors such as weight loss, improving mental health and living
longer were not identified as important determinates of sports
participation at the World Masters level.