Improved Biogeography-Based Optimization Based on Affinity Propagation

Wang, Wenwen; Liu, Peiyu; Ren, Min; Yang, Yuhao; Tian, Xin

doi:10.3390/ijgi5080129

Cited by 6 publications

(6 citation statements)

References 27 publications

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“…If the probability Pm is very low, the considered solution will has more possibility to be newly updated. Therefore, the mutation rate of an individual solution can be calculated using species count probability, given by [27]: The emigration and immigration rates are equal when the number of species is equal to S 0 . This equilibrium point presents the balance between the immigration of the new species and the extinction of the old species [25].…”

Section: Mutation Operationmentioning

confidence: 99%

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Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems

et al. 2019

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This paper presents an effective biogeography-based optimization (BBO) for optimal location and sizing of solar photovoltaic distributed generation (PVDG) units to reduce power losses while maintaining voltage profile and voltage harmonic distortion at the limits. This applied algorithm was motivated by biogeography, that the study of the distribution of biological species through time and space. This technique is able to expand the searching space and retain good solution group at each generation. Therefore, the applied method can significantly improve performance. The effectiveness of the applied algorithm is validated by testing it on IEEE 33-bus and IEEE 69-bus radial distribution systems. The obtained results are compared with the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the artificial bee colony algorithm (ABC). As a result, the applied algorithm offers better solution quality and accuracy with faster convergence.

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Section: Mutation Operationmentioning

confidence: 99%

Section: Mutation Operationmentioning

confidence: 99%

Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems

et al. 2019

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“…Jehad Ababneh has introduced combined scheme of greedy Particle Swarm Optimization (GPSO) and BBO to solve global optimization problems and further proved the efficiency of this algorithm by utilizing upon standard benchmark test functions [16]. In 2017, a Memetic Based BBO (MBBO) algorithm has been proposed by Wang et al, which uses the strategy of Affinity Propagation (AP) to modify the migration operation of the BBO algorithm and based on the memetic frame, with SA as the local search strategy [17].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid SCA Inspired BBO for Feature Selection Problems

Sindhu

Ngadiran

Yacob

et al. 2019

Mathematical Problems in Engineering

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Recent trend of research is to hybridize two and more metaheuristics algorithms to obtain superior solution in the field of optimization problems. This paper proposes a newly developed wrapper-based feature selection method based on the hybridization of Biogeography Based Optimization (BBO) and Sine Cosine Algorithm (SCA) for handling feature selection problems. The position update mechanism of SCA algorithm is introduced into the BBO algorithm to enhance the diversity among the habitats. In BBO, the mutation operator is got rid of and instead of it, a position update mechanism of SCA algorithm is applied after the migration operator, to enhance the global search ability of Basic BBO. This mechanism tends to produce the highly fit solutions in the upcoming iterations, which results in the improved diversity of habitats. The performance of this Improved BBO (IBBO) algorithm is investigated using fourteen benchmark datasets. Experimental results of IBBO are compared with eight other search algorithms. The results show that IBBO is able to outperform the other algorithms in majority of the datasets. Furthermore, the strength of IBBO is proved through various numerical experiments like statistical analysis, convergence curves, ranking methods, and test functions. The results of the simulation have revealed that IBBO has produced very competitive and promising results, compared to the other search algorithms.

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“…This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes, such as: (i) species variability over space [4][5][6][7][8][9][10][11]; and (ii) landscape dynamics [12,13].…”

mentioning

confidence: 99%

“…In such a case, relying on the variability of landscape-scale spatial patterns derived from remote sensing or geographical data (e.g., Rocchini and Di Rita [14]), might represent a powerful indicator to estimate the current status of ecosystems, considering different issues such as ecosystem mapping [12] or improved biogeography-based optimisation [13].…”

mentioning

confidence: 99%

Space-Ruled Ecological Processes: Introduction to the Special Issue on Spatial Ecology

Rocchini

2018

IJGI

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This special issue explores most of the scientific issues related to spatial ecology and its integration with geographical information at different spatial and temporal scales. Papers are mainly related to challenging aspects of species variability over space and landscape dynamics, providing a benchmark for future exploration on this theme.The need for a spatial view in Ecology is a fact. Dealing with ecological changes over space and time represents a long-lasting theme, now faced by means of innovative techniques and modelling approaches (e.g., Chaudhary et al.This special issue explores some of them, with challenging ideas facing different components of spatial patterns related to ecological processes, such as: (i) species variability over space [4][5][6][7][8][9][10][11]; and (ii) landscape dynamics [12,13].Concerning biodiversity variability over space, key spatial datasets are needed to fully investigate biodiversity change in space and time, as shown by Geri et al. [7], who carried out innovative procedures to recover and properly map historical floristic and vegetation data for biodiversity monitoring. Furthermore, Dubois et al. [6] describe in detail one of the most important integrated observatory (Digital Observatory for Protected Areas, DOPA) to mobilize and use biodiversity data and spatial datasets, to asses the ecological status of protected areas.Once such data are gathered and integrated in a proper manner, Species Distribution Modelling is certainly one of the most powerful techniques used in ecology in which the geographical component makes the difference. In this special issue, Costa et al. [5] show that species misidentification might severely impact species distribution models once dealing with presence-only data.Besides identification problems, the model being used can lead to different results. Rodriguez de Rivera and Lopez-Quilez [10] propose a comparison among different species distribution models for forest inventories, promoting high flexibility models like additive models. In this view, one of the best models to study the spatial variability of species and communities is presented in this special issue by Leitao et al. [8], who demonstrate the power of Sparse Generalized Dissimilarity Modelling, by also providing a detailed description of the newly published R package sgdm.On the other side, species richness patterns are also considered, facing water-energy dynamics on terrestrial mammal and amphibian species over wide geographical regions [11]. Beside the water-energy concept, remotely sensed spectral indices are used in this special issue to estimate different attributes of tropical forest vegetation under different anthropogenic impact [4].Species distribution modelling-like techniques might also be applied to the spread of diseases threatening key species. For instance, Makori et al. [9] predict the spatial distribution of key honeybee pests in Kenya.In some cases, species-related data on distributions are not available. In such a case, relying on the variability of landscape-sc...

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Improved Biogeography-Based Optimization Based on Affinity Propagation

Cited by 6 publications

References 27 publications

Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems

Determination of Optimal Location and Sizing of Solar Photovoltaic Distribution Generation Units in Radial Distribution Systems

A Hybrid SCA Inspired BBO for Feature Selection Problems

Space-Ruled Ecological Processes: Introduction to the Special Issue on Spatial Ecology

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