On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

Genetic signature of the northward expansion of the Egyptian mongoose Herpestes ichneumon (Herpestidae) in the Iberian Peninsula

In the last three decades, the range of the Egyptian mongoose (Herpestes ichneumon) has increased in the Iberian Peninsula. A panel of microsatellites was used to confront the patterns of genetic diversity of the species with the scenario of its recent northward expansion in its Iberian range. Evidence of substructure and significant genetic differentiation within the studied population were recorded, with a central-northern subpopulation (CNorth) and a southern subpopulation (S). Northward range expansion was supported by the observed allelic frequencies, diversity parameters, and observed heterozygosity of the studied loci, with S showing a higher allelic diversity and a higher number of private alleles than CNorth. Patterns of isolation-by-distance and isolation-by-barrier as a result of the Tagus River were demonstrated, suggesting that the river acted as a semi-permeable barrier, possibly leading to genetic differentiation of the studied population. The observed individuals from CNorth in southern locations and individuals from S in central/northern areas might comprise evidence for long range dispersals across the studied range. A bottleneck event after population expansion was supported by a significant heterozygosity deficiency in CNorth, which is in agreement with a scenario of founder events occurring in recently colonized areas after the crossing of the Tagus River.

A Comparative Analysis Between Genetic Algorithms and Complex Nonlinear Least Squares on Electrical Impedance Characterization

This paper compares the performance of the complex nonlinear least squares algorithm implemented in the LEVM/LEVMW software with the performance of a genetic algorithm in the characterization of an electrical impedance of known topology. The effect of the number of measured frequency points and of measurement uncertainty on the estimation of circuit parameters is presented. The analysis is performed on the equivalent circuit impedance of a humidity sensor.

Circadian Phase Control - Genetic Algorithm and Non-linear Control Approach

This paper deals with the phase control for Neurospora circadian rhythm. The nonlinear control, given by tuning the parameters (considered as controlled variables) in Neurospora dynamical model, allows the circadian rhythms tracking a reference one. When there are many parameters (e.g. 3 parameters in this paper) and their values are unknown, the adaptive control law reveals its weakness since the parameters converging and control objective must be guaranteed at the same time. We show that this problem can be solved using the genetic algorithm for parameters estimation. Once the unknown parameters are known, the phase control is performed by chaos synchronization technique.