The purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where he was in 1999 Normalized Difference Vegetation Index (NDVI) 925km2 and Normalized Difference Water Index (NDWI) 75.3 km2 In the case of an increase during the growth period, while the values decreased during the period of dry to (NDVI) 390.8 km2 and (NDWI) 51.9 km2. As for Soil Adjusted Vegetation Index (SAVI) 1692.9 km2 and Normalized Difference Built up Index (NDBI) 782.1 km2 we notice a decrease in the growth period, while the values increase during the dry period to (SAVI) 2239.1 km2 and (NDBI) 1495.7 km2. In 2021 (NDVI) 242.7 km2 (NDWI) 83.4 km2 in the case of an increase during the growth period, while the values decreased during the period of dry to (NDVI) 122.2 km2 and (NDWI) 73.2 km2. As for (SAVI) 3016.3 km2 (NDBI) 1263.3 km2 we notice a decrease in the growth period, while the values increase during the dry period to (SAVI) 3702.3 km2 and (NDBI) 1882.2 km2
In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho
... Show MoreThis paper consist some new generalizations of some definitions such: j-ω-closure converge to a point, j-ω-closure directed toward a set, almost j-ω-converges to a set, almost j-ω-cluster point, a set j-ω-H-closed relative, j-ω-closure continuous mappings, j-ω-weakly continuous mappings, j-ω-compact mappings, j-ω-rigid a set, almost j-ω-closed mappings and j-ω-perfect mappings. Also, we prove several results concerning it, where j Î{q, δ,a, pre, b, b}.
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