An Artificial Intelligence based Model for Optimal Exploratory Surveys

Aref Shirazi

ISBN 10: 6208012783 / ISBN 13: 9786208012786

Editore: LAP LAMBERT Academic Publishing Dez 2024, 2024

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Neuware -exploratory surveys (geochemical and geophysical) are important and basic steps in the mineral exploration; The importance of this stage includes several reasons that are intertwined; First, the precision and accuracy of the measured data compared to the investigated community, whether they are representative of it or not, and can the data be used as representative of the community in future studies Second, the density of exploratory surveys that is directly related to management resources (Time, cost, human and equipment); Third, the exact location of the exploration, which must be purposefully selected, so that optimal results can be obtained by spending the least amount of resources.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch.

Codice articolo 9786208012786

Dati bibliografici

• Titolo: An Artificial Intelligence based Model for Optimal Exploratory Surveys
• Editore: LAP LAMBERT Academic Publishing Dez 2024
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 10: 6208012783
• ISBN 13: 9786208012786
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 220 L x 150 A x 5 P (millimetri) 220 millimetri di larghezza per 150 millimetri di altezza per 5 millimetri di profondità
• Peso: 119 grammi

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Riassunto

exploratory surveys (geochemical and geophysical) are important and basic steps in the mineral exploration; The importance of this stage includes several reasons that are intertwined; First, the precision and accuracy of the measured data compared to the investigated community, whether they are representative of it or not, and can the data be used as representative of the community in future studies? Second, the density of exploratory surveys that is directly related to management resources (Time, cost, human and equipment); Third, the exact location of the exploration, which must be purposefully selected, so that optimal results can be obtained by spending the least amount of resources.