Intelligent Decision Making Through Bio-Inspired Optimization

Name: Intelligent Decision Making Through Bio-Inspired Optimization
Brand: IGI Global
SKU: 9798369346921
Price: 111468 HUF
Availability: InStock

Szerző: Shilpa Mehta, Ram Krishan

Nyelv:

Kötés: Puha kötésű

Kiadó: IGI Global

Elérhetőség: Beszállítói készleten

Küldés 10-18 napon belül

111 468 Ft

Academic scholars, entrenched in the complexities of various domains, face the daunting task of navi...

Információk a könyvről

Szerző

Shilpa Mehta, Ram Krishan

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2024

oldal

296

EAN

9798369346921

Enbook ID

45815068

Kiadó

IGI Global

Súly

689

Méretek

216 x 279 x 16

Teljes leírás

Academic scholars, entrenched in the complexities of various domains, face the daunting task of navigating intricate decision-making scenarios. The prevailing need for efficient and effective decision-making tools becomes increasingly apparent as traditional methodologies struggle to keep pace with the demands of modern research and industry. This pivotal issue necessitates a shift, urging scholars to explore unconventional approaches that can transcend disciplinary boundaries and unlock new dimensions of problem-solving. In response to these pressing challenges, Intelligent Decision Making Through Bio-Inspired Optimization emerges as a beacon of ingenuity. This groundbreaking book transcends usual disciplinary boundaries, seamlessly integrating computer science, artificial intelligence, optimization, and decision science. Its multidisciplinary approach addresses the inherent complexities faced by scholars, offering a comprehensive exploration of nature-inspired algorithms such as genetic algorithms, swarm intelligence, and evolutionary strategies. The book's core mission is to empower academic scholars with the tools to overcome contemporary decision-making hurdles, providing a holistic understanding of these bio-inspired approaches and their potential to revolutionize the scholarly landscape.

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Intelligent Decision Making Through Bio-Inspired Optimization

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