imperialist competitive algorithm

Accurate and correct identification of vessels moving in the waters from a distance is important in many ways. Having information type of vessels more correct decisions on how to deal with them. The sounds emitted by the vessels can be distinguished from each other and it is possible to identify the vessels by their sound. Therefore, in this study, the vessels have been classified based on their weight and the sound emitted by them. In the present study, the characteristics of each of the sounds recorded the vessels were extracted using the Mel-Frequency Cepstrum Coefficients (MFCC) method, and the ability of the artificial neural network and its hybrids with the Genetic Algorithm (ANN-GA) and the Imperialist Competitive Algorithm (ANN-ICA) The results showed that artificial neural network feed forward back propagation (BP-FF) with learning functions Levenberg-Marquardt (LM), Bayesian (BR) and Resilient Backpropagation (RP) has an accuracy of 86, 96 and 82 percent respectively in assigning the features of each vessels to them. Also, ANN-GA and ANN-ICA networks showed classification accuracy equal to 94% and 77%, respectively. Finally, it can be concluded that the Artificial Neural Network with the Bayesian learning function has the ability to acceptably classify the sounds emitted the vessels and can be used in marine and military applications.

In Academic literature has recently emphasized that why urban resilience is different from urban sustainability. Urban policymakers, on the other hand, use the terms almost interchangeably. In this study by analyzing the pattern of physical-spatial resilience; Factors affecting environmental hazards such as earthquakes, subsidence, etc. are studied in areas 2 and 12 of Tehran.

This study is an applied research that has been done with case-analysis method and quantitative approach. Due to the nature of the data is descriptive. To achieve the objectives of research and analysis of physical-spatial resilience pattern affected by environmental hazards in Tehran metropolis including subsidence and earthquake, the dimensions studied in 13 indicators including base price (square meters), material, construction year, building age, building skeleton, number of floors , Degree of concentration or dispersion of residential land use, grain size, permeability, total area of ​​uses (green and open space) and area of ​​residential land use in spatial and physical part) and (degree of concentration or dispersion of population, residential clusters and open and green spaces for population based The majority of residents in the neighborhoods were extracted for the geographical direction of population distribution in the social sector (based on land use studies of the current situation). To evaluate and analyze spatial and social patterns, the colonial competition algorithm in Matlab a2019 software environment and to spatialize the studied indicators, the method (Tracking Analyst Tools) in the network analysis process (Network Analyst Tools) in ArcGIS software environment has been used.

Due to the location of District 12 in the historical context and the concentration and density of the population in the focal axes with regional performance, it shows more vulnerability. In relation to the criteria of population density, granulation as well as the skeletal condition of buildings; Overall, Zone 2 shows a better situation. Although the population density in both zones is the same despite the larger population and size of Zone 2, it shows lower resilience due to the flood of floating population visiting and living in Zone 12.

Due to the erosion of buildings and low space permeability, the pattern of spatial distribution of the population and the factors affecting the physical-spatial ruptures in Zones 2 and 12, the results show that the pattern of distribution and fracture rupture in neighborhoods are different in Zone 12. Indicates a more unstable situation.

Circular diamond sawblades and diamond wire saw have extensive applications in the processing of natural stones. The cutting performance is affected by the rock properties, sawing characteristics and working conditions. So far, many researchers focused on modeling and estimating the sawing performance. Performance prediction of sawing machine have important role in the cost estimation. The aim of present study is to develop nonlinear models for estimating cutting force in circular diamond sawblades using Imperialist Commutative Algorithm (ICA) optimization techniques and compare the results obtained from literature models. For this purposes, the conducted tests on the granitic rocks were used in the case study and the proposed models based on those data have been evaluated. The peripheral speed, traverse speed, cut depth and flow rate of cooling fluid are used to predict the cutting force. According to the calculated statistical error between the forecasted and real measured values of cutting force, ICA-based model has the lowest values of MAPE, VARE, MEDAE and RMSE, while it has the highest value of VAF, in comparison to the other models.  It is concluded that this ACII-based model is superior to others.

Gravity inversion is a classical tool in applied geophysics. Inversion of basement relief of sedimentary basins is an important application among the nonlinear techniques. Classically, local deterministic optimization techniques have been employed to solve the non-linear gravity inverse problem. Swarm intelligence algorithms, such as ant colony algorithm or particle swarm optimizers, are promising alternatives to classical inversion methods. In this study, imperialist competitive algorithm (ICA), was designed and utilized for two-dimensional (2D) gravity inversion of basement relief in sedimentary basins. Reliability of this technique was tasted by modeling of gravity data acquired from a synthetic model, and then, the synthetic model parameters were obtained from this modeling approach with acceptable accuracy. Moreover, the results of utilizing this approach on noisy data showed that this approach was robust to the presence of noise in the data. For the case of real data, this approach was applied on a real gravity profile in Atacama Desert (north Chile) and the results were confirmed with previously published works related to this area. Generally, compared to techniques already proposed for 2D nonlinear gravity inversion, the ICA technique, proposed here, appears as a powerful tool for estimating the basement relief of sedimentary basins.

Water scarcity is one of the most important issues in the 21st century that human societies encounter. Population growth, industrial and agricultural production, rapid urbanization, and severe climate change have had a major impact on limited water resources and the environment in river basins. The optimal allocation of water resources among consumers requires effective measurements of water resources and its integrated management for human and environmental justice. Optimization of water resource allocation is a very complex decision to make in several levels, stages, subjects, objectives, and non-linear communications. With the complexity of water allocation issues, its algorithms have been gradually improved, and the use of intelligent meta-analysis algorithms in optimizing the allocation of water resources from traditional math planning has surpassed. However, the effectiveness of conventional optimization algorithms is not ideal from a variety of perspectives, and issues such as convergence, computational speed, initial sensitivity, etc., due to the complexity and multi-purpose of optimizing water allocation, require further studies to improve the efficiency of the algorithm and obtaining a desirable overall solution.

The gray wolf algorithm mimics the hierarchy of leadership and the mechanism of hunting gray wolves in nature. In this algorithm, four types of gray wolves, including alpha, beta, delta, and omega have been used to simulate a hierarchy of leadership. Also, the colonial competition algorithm begins with some primary random populations, each of which is called a "country". Some of the best population elements (equivalent to the elites in the genetic algorithm) are chosen as imperialists. The remaining population is considered as a colony. Colonialists, depending on their power, are pulling these colonies into a particular process. In this research, the gray wolf and colonial competition algorithms were used to optimize water resources values during 2000-2012 regarding the Sofi-Chay irrigation and drainage network and Alavian dam to achieve the optimal policy. The Alavian dam in the province of East Azerbaijan, 3km north of Maragheh city, near the village of Alavian, has been constructed on the Sofi-Chai River, and supplies drinking water to the Maragheh, Miandoab, Bonab, Ajbashir, and Malekan counties.

The results of the implementation of the gray wolf algorithm, compared to the colonial competition algorithm, were very close to the measured value of the amount of allocated water and this suggests the coherence and efficiency of the gray wolf algorithm in water resources system. According to the RMSE values in all four areas, the gray wolf algorithm was 44% less than the colonial competition algorithm and 64% higher in the Nash-Sutcliff coefficient.

The results of this study showed that the gray wolf algorithm has a suitable speed for finding the optimal response. In other words, it has a high convergence rate and can find an optimal global optimization problem. The results showed that the gray wolf algorithm yielded better and more acceptable results in water utilization in combination with utilizing surface water and underground water resources.