Author: haroonkhan
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Systems Engineering Approach Has Achieved Global Recognition
The SE approach has achieved remarkable results in diverse fields, such as airplane development, major construction projects, the automobile industry, large shipping business operations, natural resource utilization, environmental protection, economic system reform, and many scientific research projects worldwide. SE plays an important role and it is widely recognized and accepted by many global leaders and…
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Systems Engineering Is a Multidisciplinary Approach
SE is a multidisciplinary approach to planning, organizing, coordinating, and controlling production, construction, transportation, storage, communications, commerce, scientific research, and other human activities. In general SE, starting with the overall concept of a system, studies the various subsystems/components, analyzes the relationship between various functions, and uses mathematical methods to find the best solution to build…
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Systems Engineering Is an Emerging Science
SE is an emerging science that studies systems and is an engineering technique for designing and building a complex product. Building a new complex product requires the use of quantitative analysis (including modeling, simulation, and optimization methods) or quantitative/qualitative analysis of a combination of methods, along with system analysis and system design of the product. The…
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Systems Engineering Requires System Thinking
Systems engineering can be viewed as a collective effort incorporating a large group of engineering techniques that directly transforms the objective world using system thinking. A system is composed of several key components that are related to each other and that interact with each other. People’s understanding of a system, that is, their thinking about…
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Systems Engineering Definitions
Systems Engineering: A Team Approach Systems engineering (SE) is a multidisciplinary approach to product lifecycle realization. SE allows one to better understand each product as a whole and to improve the planning, design/development, manufacturing, and maintenance processes. Organizations use SE to model and analyze the interactions, needs, subsystems, constraints, and interactions among system components and…
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Nonhierarchical clustering: k-means
The best-known method in the class of nonhierarchical clustering algorithms is the k-means approach. In the k-means method, unlike with the hierarchical ones, observations can be moved from one cluster to another in order to minimize a joint measure of the quality of clustering; hence, the method is iterative in nature. The starting point is the selection of k seeds,…
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Hierarchical methods
A first class of approaches to cluster formation is based on the sequential construction of a tree (dendrogram), that leads us to form clusters; Fig. 17.5 shows a simple dendrogram. The leaves of the tree correspond to objects; branches of the tree correspond to sequential groupings of observations and clusters. Since a tree suggests a natural hierarchy,…
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Measuring distance
Given two observations , we may define various distance measures between them, such as Other distances may be defined to account for categorical variables; we may also assign weights to variables to express their relative importance. These distances measure the dissimilarity between two single observations, but when we aggregate several observations into clusters, we need some…
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CLUSTER ANALYSIS
The aim of cluster analysis is to search for patterns in a dataset by grouping similar items. The number of groups (clusters) need not be fixed in advance, and, in fact, there is an array of different methods, which share a common need: the definition of a distance between observations, which is used to measure…
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FACTOR ANALYSIS
The rationale behind factor analysis may be best understood by a small numerical example. Example 17.2 Consider observations in and the correlation matrix of their component variables X1, X2, …, X5: Does this suggest some structure? We see that X1 and X2 seem to be strongly correlated with each other, whereas they seem weekly correlated with X3, X4, and X5. The latter variables, on the contrary, seem…