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Anthropogenic impact on the distribution of the birds in the tropical thorn forest, Punjab, Pakistan
Muhammad Altaf,Arshad Javid,Abdul Majid Khan,M.S.H. Khan,Muhammad Umair,Zulfiqar Ali 국립중앙과학관 2018 Journal of Asia-Pacific Biodiversity Vol.11 No.2
The present research was conducted to assess the anthropogenic impacts on avian diversity around the river Chenab, Pakistan. The avian diversity was recorded on different landscapes along the river Chenab, that is, forest, agricultural, rural, and urban habitats. The data on diversity and distribution of various avian species were collected through linear count along with direct count methods viz. personal observations and sound records and indirect count methods viz. presences of carcasses and meeting with local communities. The habitat preferences of birds varied significantly. A decline in avian diversity was observed from forest habitat to urban landscapes. One year of bird surveys compiled a total of 150 species from all habitats along the river Chenab. Computed statistical data show that Shannon's index provides a quantitative report of diversity which was highest at forest habitat (4.261) followed by rural forest habitat (3.746), agri–rural habitat (3.746), agriculture habitat (3.623), WLH (2.723), urban vegetative habitat (3.215), and very least at urban nonvegetative habitat (2.247). It can be concluded from the present study that many of the avian species have specific habitats and also noted that corridors and connections among different landscapes are important for the conservation of avian diversity.
Solving the Travelling Salesman Problem Using an Ant Colony System Algorithm
Zakir Hussain Ahmed,Majid Yousefikhoshbakht,Abdul Khader Jilani Saudagar,Shakir Khan International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.2
The travelling salesman problem (TSP) is an important combinatorial optimization problem that is used in several engineering science branches and has drawn interest to several researchers and scientists. In this problem, a salesman from an arbitrary node, called the warehouse, starts moving and returns to the warehouse after visiting n clients, given that each client is visited only once. The objective in this problem is to find the route with the least cost to the salesman. In this study, a meta-based ant colony system algorithm (ACSA) is suggested to find solution to the TSP that does not use local pheromone update. This algorithm uses the global pheromone update and new heuristic information. Further, pheromone evaporation coefficients are used in search space of the problem as diversification. This modification allows the algorithm to escape local optimization points as much as possible. In addition, 3-opt local search is used as an intensification mechanism for more quality. The effectiveness of the suggested algorithm is assessed on a several standard problem instances. The results show the power of the suggested algorithm which could find quality solutions with a small gap, between obtained solution and optimal solution, of 1%. Additionally, the results in contrast with other algorithms show the appropriate quality of competitiveness of our proposed ACSA.