Privacy Preservation in Utility Mining Based on Genetic Algorithm: A New Approach

Author(s):  
Sugandha Rathi ◽  
Rishi Soni
Author(s):  
Ganesh Marotrao KAKANDIKAR ◽  
Vilas M. NANDEDKAR

Forming is a compression-tension process involving wide spectrum of operations and flow conditions. The result of the process depends on the large number of parameters and their interdependence. The selection of various parameters is still based on trial and error methods. In this paper the authors presents a new approach to optimize the geometry parameters of circular components, process parameters such as blank holder pressure and coefficient of friction etc. The optimization problem has been formulated with the objective of optimizing the maximum forming load required in Forming. Genetic algorithm is used for the optimization purpose to minimize the drawing load and to optimize the process parameters. A finite element analysis simulation software Fast Form Advanced is used for the validations of the results after optimization.


At present, there is no precise method that can inform where the lost flight MH370 is. This chapter proposes a new approach to search for the missing flight MH370. To this end, multiobjective genetic algorithms are implemented. In this regard, a genetic algorithm is taken into consideration to optimize the MH370 debris that is notably based on the geometrical shapes and spectral signatures. Currently, there may be three limitations to optical remote sensing technique: (1) strength constraints of the spacecraft permit about two hours of scanning consistently within the day, (2) cloud cover prevents unique observations, and (3) moderate information from close to the ocean surface is sensed through the scanner. Needless to say that the objects that are spotted by different satellite data do not scientifically belong to the MH370 debris and could be just man-made without accurate identifications.


Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1243 ◽  
Author(s):  
Riccardo Cecchetti ◽  
Francesco de Paulis ◽  
Carlo Olivieri ◽  
Antonio Orlandi ◽  
Markus Buecker

An iterative optimization for decoupling capacitor placement on a power delivery network (PDN) is presented based on Genetic Algorithm (GA) and Artificial Neural Network (ANN). The ANN is first trained by an appropriate set of results obtained by a commercial simulator. Once the ANN is ready, it is used within an iterative GA process to place a minimum number of decoupling capacitors for minimizing the differences between the input impedance at one or more location, and the required target impedance. The combined GA–ANN process is shown to effectively provide results consistent with those obtained by a longer optimization based on commercial simulators. With the new approach the accuracy of the results remains at the same level, but the computational time is reduced by at least 30 times. Two test cases have been considered for validating the proposed approach, with the second one also being compared by experimental measurements.


Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3806 ◽  
Author(s):  
Rafał Wiśniowski ◽  
Paweł Łopata ◽  
Grzegorz Orłowicz

Advances in the field of material engineering, computerization, automation, and equipment miniaturization enable modernization of the existing technologies and development of new solutions for construction, inspection, and renovation of underground pipelines. Underground pipe installations are used in the energy sector, gas industry, telecommunications, water and sewage transport, heating, chemical industry, and environmental engineering. In order to build new pipeline networks, dig and no-dig techniques are used. Horizontal Directional Drilling (HDD) is one of the most popular trenchless technologies. The effectiveness of HDD technology application is mostly determined by its properly designed trajectory. Drilling failures and complications, which often accompany the application of the HDD technology, result from poor design of the well path in relation to the existing geological and drilling conditions. The article presented two concepts of Horizontal Directional Drilling well path trajectory design: Classic sectional, which is a combination of straight and curvilinear sections, and a single-section chain curve trajectory (catenary). Taking into account the advantages and disadvantages of the catenary trajectory relative to the sectional trajectory, the author’s solution was presented, which was the implementation of the sectional trajectory with a maximum shape similarity to the catenary trajectory. The new approach allowed us to take advantage of a chain curve trajectory and was easier to implement using the available technology. The least squares method, based on deviations from a catenary trajectory, was set as the matching criterion. The process of searching for a trajectory, being a combination of straight and curvilinear sections as similar as possible to a catenary-type trajectory, was carried out using two methodologies: State space search and a genetic algorithm. The article shows the pros and cons of both optimization methodologies. Taking into account the technical and technological limitations of HDD drilling devices, a new approach was proposed, combining the methodology of state space search with the genetic algorithm. A calculation example showed the application of the proposed methodology in an engineering design process.


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