The Analysis of Peculiar Control Parameters of Artificial Bee Colony Algorithm on the Numerical Optimization Problems

Artificial bee colony (ABC) algorithm is one of the popular swarm intelligence algorithms. ABC has been developed by being inspired foraging and waggle dance behaviors of real bee colonies in 2005. Since its invention in 2005, many ABC models have been proposed in order to solve different optimization problems. In all the models proposed, there are only one scout bee and a constant limit value used as control parameters for the bee population. In this study, the performance of ABC algorithm on the numeric optimization problems was analyzed by using different number of scout bees and limit values. Experimental results show that the results obtained by using more than one scout bee and different limit values, are better than the results of basic ABC. Therefore, the control parameters of the basic ABC should be tuned according to given class of optimization problems. In this paper, we propose reasonable value ranges of control parameters for the basic ABC in order to obtain better results on the numeric optimization problems.

Investigation and Implementation of a PIC-Based Sensor Node for Wireless Sensor Networks

The basic component of wireless sensor networks is sensor node, and it is one of the most investigated complex issues in wireless sensor networks. Within this investigation concept, one of the major topics focused on wireless sensor networks is designing sensor node equipment. In this study, a new wireless sensor node design was proposed. In this design, a low-power PIC and a low-power transceiver-receiver device were used. In order to connect various sensors to the node, an expansion slot was designed. The software that runs on the microcontroller was written in the PIC-C language, and it could be adapted for different routing algorithms and sensor types. So this paper presents an alternative low cost and low powered sensor node design and implementation for usage of the researchers and practitioners.

Petro Gram: An excel-based petrology program for modeling of magmatic processes

Petro Gram is an Excel?based magmatic petrology program that generates numerical and graphical models.Petro Gram can model the magmatic processes such as melting,crystallization,assimilation and magma mixing based on the trace element and isotopic data.The program can produce both inverse and forward geochemical models for melting processes(e.g.forward model for batch,fractional and dynamic melting,and inverse model for batch and dynamic melting).However,the program uses a forward modeling approach for magma differentiation processes such as crystallization(EC:Equilibruim Crystallization,FC:Fractional Crystallization,IFC:Imperfect Fractional Crystallization and In-situ Crystallization),assimilation(AFC:Assimilation Fractional Crystallization,Decoupled FC-A:Decoupled Fractional Crystallization and Assimillation,A-IFC:Assimilation and Imperfect Fractional Crystallization)and magma mixing.One of the most important advantages of the program is that the melt composition obtained from any partial melting model can be used as a starting composition of the crystallization,assimilation and magma mixing.In addition,Petro Gram is able to carry out the classification,tectonic setting,multi-element(spider)and isotope correlation diagrams,and basic calculations including Mg^#,Eu/Eu^*,εSrandεNdwidely used in magmatic petrology.