Statistical Mechanics Approximation of Biogeography-Based Optimization

2016 ◽  
Vol 24 (3) ◽  
pp. 427-458 ◽  
Author(s):  
Haiping Ma ◽  
Dan Simon ◽  
Minrui Fei

Biogeography-based optimization (BBO) is an evolutionary algorithm inspired by biogeography, which is the study of the migration of species between habitats. This paper derives a mathematical description of the dynamics of BBO based on ideas from statistical mechanics. Rather than trying to exactly predict the evolution of the population, statistical mechanics methods describe the evolution of statistical properties of the population fitness. This paper uses the one-max problem, which has only one optimum and whose fitness function is the number of 1s in a binary string, to derive equations that predict the statistical properties of BBO each generation in terms of those of the previous generation. These equations reveal the effect of migration and mutation on the population fitness dynamics of BBO. The results obtained in this paper are similar to those for the simple genetic algorithm with selection and mutation. The paper also derives equations for the population fitness dynamics of general separable functions, and we find that the results obtained for separable functions are the same as those for the one-max problem. The statistical mechanics theory of BBO is shown to be in good agreement with simulation.

2010 ◽  
Vol 19 (01) ◽  
pp. 107-121 ◽  
Author(s):  
JUAN CARLOS FIGUEROA GARCÍA ◽  
DUSKO KALENATIC ◽  
CESAR AMILCAR LÓPEZ BELLO

This paper presents a proposal based on an evolutionary algorithm for imputing missing observations in time series. A genetic algorithm based on the minimization of an error function derived from their autocorrelation function, mean, and variance is presented. All methodological aspects of the genetic structure are presented. An extended description of the design of the fitness function is provided. Four application examples are provided and solved by using the proposed method.


2008 ◽  
Vol 19 (07) ◽  
pp. 1047-1062 ◽  
Author(s):  
ADIL AMIRJANOV

One way to improve a search strategy in a Genetic Algorithm (GA) is to reduce the search space towards the feasible region where the global optimum is located. The paper describes the effect of an adjustment of a search space size of GA on the macroscopic statistical properties of population such as the average fitness and the variance fitness of population. The set of equations of motion was derived for the one-max problem that expressed the macroscopic statistical properties of population after an adjustment of a search space size in terms of those prior to the operation.


2019 ◽  
Author(s):  
Chem Int

The genetic algorithm, based on the Multi-Niche Crowding (MNC) method, coupled with the semi-empirical AM1 method is used to analyze the potential energy surface of some polypeptides containing cysteine. Calculating the formation energies of these systems in both neutral and deprotonated states, we deducted their enthalpy of deprotonation (ΔHacid) and we identified the types of rearrangement of these systems when isolated. Deprotonation occurs at the level of the alone acid site characterizing these peptides namely the thiol. The values obtained for the deprotonation enthalpies of polypeptides AlaCysNH2, Ala2CysNH2, Ala3CysNH2, Ala4CysNH2, CysAlaNH2 and CysAla2NH2 are in the order of 331.3 kcal/mol, 322.9 kcal/mol, 313.8 kcal/mol, 312.9 kcal/mol, 325.1 kcal/mol and 317.3 kcal/mol, respectively. The location of global and local minima of these polypeptides shows that they are rearranged in two forms of secondary structures namely helical and globular forms. The obtained results are in good agreement with the experimental ones, on the one hand, and with those from other methods in the theoretical calculation, on the other hand. Therefore, the N-cysteine is more acidic than their homologous C-Cysteine and for this series of plolyalanines, the acidity in the gas phase increased with the peptide chain length.


2005 ◽  
Vol 05 (03) ◽  
pp. 595-616 ◽  
Author(s):  
NAWWAF KHARMA ◽  
CHING Y. SUEN ◽  
PEI F. GUO

The main objective of Project PalmPrints is to develop and demonstrate a special co-evolutionary genetic algorithm (GA) that optimizes (a clustering fitness function) with respect to three quantities, (a) the dimensions of the clustering space; (b) the number of clusters; and (c) and the locations of the various clusters. This genetic algorithm is applied to the specific practical problem of hand image clustering, with success. In addition to the above, this research effort makes the following contributions: (i) a CD database of (raw and processed) right-hand images; (ii) a number of novel features designed specifically for hand image classification; (iii) an extended fitness function, which is particularly suited to a dynamic (i.e. dimensionality varying) clustering space. Despite the complexity of the multi-optimizational task, the results of this study are clear. The GA succeeded in achieving a maximum fitness value of 99.1%; while reducing the number of dimensions (features) of the space by more than half (from 84 to 41).


Author(s):  
R. Fürth

An attempt is made to develop the statistical mechanics of the liquid state based not on the usual concept of a “radial distribution function” but on that of a “next neighbour distribution function” which is closely linked up with Bernal's ideas on the characteristic features of liquid structure. Making certain simplifying assumptions it is indeed possible to construct a partition function for an atomic liquid in this way and from this to derive the thermodynamic properties of the system according to the principles of classical statistical mechanics. It is shown that the free energy, the equation of state, the specific heat and entropy as obtained from the theory are consistent with the expected behaviour of such liquids. It is further shown that the computed next neighbour distribution function for close packing is in good agreement with the one derived empirically from a model by Bernal and Mason.


2019 ◽  
Vol 67 (6) ◽  
pp. 483-492
Author(s):  
Seonghyeon Baek ◽  
Iljae Lee

The effects of leakage and blockage on the acoustic performance of particle filters have been examined by using one-dimensional acoustic analysis and experimental methods. First, the transfer matrix of a filter system connected to inlet and outlet pipes with conical sections is measured using a two-load method. Then, the transfer matrix of a particle filter only is extracted from the experiments by applying inverse matrices of the conical sections. In the analytical approaches, the one-dimensional acoustic model for the leakage between the filter and the housing is developed. The predicted transmission loss shows a good agreement with the experimental results. Compared to the baseline, the leakage between the filter and housing increases transmission loss at a certain frequency and its harmonics. In addition, the transmission loss for the system with a partially blocked filter is measured. The blockage of the filter also increases the transmission loss at higher frequencies. For the simplicity of experiments to identify the leakage and blockage, the reflection coefficients at the inlet of the filter system have been measured using two different downstream conditions: open pipe and highly absorptive terminations. The experiments show that with highly absorptive terminations, it is easier to see the difference between the baseline and the defects.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 115
Author(s):  
Andriy Chaban ◽  
Marek Lis ◽  
Andrzej Szafraniec ◽  
Radoslaw Jedynak

Genetic algorithms are used to parameter identification of the model of oscillatory processes in complicated motion transmission of electric drives containing long elastic shafts as systems of distributed mechanical parameters. Shaft equations are generated on the basis of a modified Hamilton–Ostrogradski principle, which serves as the foundation to analyse the lumped parameter system and distributed parameter system. They serve to compute basic functions of analytical mechanics of velocity continuum and rotational angles of shaft elements. It is demonstrated that the application of the distributed parameter method to multi-mass rotational systems, that contain long elastic elements and complicated control systems, is not always possible. The genetic algorithm is applied to determine the coefficients of approximation the system of Rotational Transmission with Elastic Shaft by equivalent differential equations. The fitness function is determined as least-square error. The obtained results confirm that application of the genetic algorithms allow one to replace the use of a complicated distributed parameter model of mechanical system by a considerably simpler model, and to eliminate sophisticated calculation procedures and identification of boundary conditions for wave motion equations of long elastic elements.


Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1581
Author(s):  
Alfonso Hernández ◽  
Aitor Muñoyerro ◽  
Mónica Urízar ◽  
Enrique Amezua

In this paper, an optimization procedure for path generation synthesis of the slider-crank mechanism will be presented. The proposed approach is based on a hybrid strategy, mixing local and global optimization techniques. Regarding the local optimization scheme, based on the null gradient condition, a novel methodology to solve the resulting non-linear equations is developed. The solving procedure consists of decoupling two subsystems of equations which can be solved separately and following an iterative process. In relation to the global technique, a multi-start method based on a genetic algorithm is implemented. The fitness function incorporated in the genetic algorithm will take as arguments the set of dimensional parameters of the slider-crank mechanism. Several illustrative examples will prove the validity of the proposed optimization methodology, in some cases achieving an even better result compared to mechanisms with a higher number of dimensional parameters, such as the four-bar mechanism or the Watt’s mechanism.


2021 ◽  
Vol 11 (3) ◽  
pp. 1243
Author(s):  
Hongseok Jeong ◽  
Jeung-Hoon Lee ◽  
Yong-Hyun Kim ◽  
Hanshin Seol

The dominant underwater noise source of a ship is known to be propeller cavitation. Recently, attempts have been made to quantify the source strength using on-board pressure sensors near the propeller, as this has advantages over conventional noise measurement. In this study, a beamforming method was used to estimate the source strength of a cavitating propeller. The method was validated against a model-scale measurement in a cavitation tunnel, which showed good agreement between the measured and estimated source levels. The method was also applied to a full-scale measurement, in which the source level was measured using an external hydrophone array. The estimated source level using the hull pressure sensors showed good agreement with the measured one above 400 Hz, which shows potential for noise monitoring using on-board sensors. A parametric study was carried out to check the practicality of the method. From the results, it was shown that a sufficient recording time is required to obtain a consistent level at high frequencies. Changing the frequency resolution had little effect on the result, as long as enough data were provided for the one-third octave band conversion. The number of sensors affected the mid- to low-frequency data.


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