Tribal Area Development Planning of Chintapalli Block, Visakhapatnam District, Andhra Pradesh, India: Using GIS and Remote Sensing Approach
Author(s)– Prakasam. C , Kartic Kumar , Sunam Chatterjee
Tribal area Developmental planning implies prudent use of all the natural resources to ensure optimum and sustained productivity. In this approach the basic unit of development is a watershed, which is a manageable hydrological unit and the development is not just confined to agricultural lands alone, but covers the area, starting from the highest point of the area to the outlet of the natural stream. This calls for maintaining the fragile balance between productivity functions and conservation practices through monitoring and identification of problem areas and implementation of location specific development plans. Reliability of the data bases, both the spatial and non-spatial, is therefore crucial to the success of the developmental planning. Equally important is the timely inflow of information to serve planning needs. Satellite based remote sensing has emerged as a powerful tool for planning watershed developmental programmes. Further, Geographic Information System (GIS) is required for integration of different thematic resources. Geographic Information System is an analytical tool capable to perform storing, spatial operations, spatial queries, data linkages, data matching and output generation. Thus, in the present study, the latest technologies such as remote sensing and GIS are employed for generation of tribal area development planning of chintapalli block of Visakhapatnam district, Andhra Pradesh State.
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Structural Optimization Using a Novel Genetic Algorithm for Rapid Convergence
Author(s)– M. A. Al-Shihri
A novel evolutionary algorithm based upon genetic algorithm is presented in this paper which is suitable for a general class of structural optimization problems. The algorithm is applicable for discrete and/or continuous type(s) of design variables. Proposed algorithm has been designed such that it converges rapidly to local optima whenever a local optimum solution is nearby. In each generation, the algorithm selects a chromosome from the population that represents a design close to a local optimum. Further, a new set of chromosomes called Single Digit Chromosome (SDC) are generated having all zero bits except for one. Chromosomes are selected from the population and their binary addition and subtraction are performed with the SDCs. Through a number of test examples it is shown that the proposed algorithm is much robust and reliable as compared to the traditional genetic algorithm.
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I am pleased to inform you that the following journals from Integrated Publishing have been found suitable for inclusion in the CAS database:
Journal of Applied Engineering Research (ISSN: 0976-4259)
Journal of Civil and Structural Engineering (ISSN: 0976-4399)
Journal of Environmental Sciences (ISSN: 0976-4402)
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