SPIR 发表于 2025-3-21 16:59:55

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FATAL 发表于 2025-3-21 21:40:49

B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasfe and minimizes energy consumption for an underwater sensor network. The optimization algorithm uses the following state parameters to estimate network lifetime: (1) internode distance; (2) transmission frequency; (3) sampling frequency; and (4) number of descendants in the routing tree. Transmissi

杀菌剂 发表于 2025-3-22 02:32:19

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GAVEL 发表于 2025-3-22 05:45:23

B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasfe and minimizes energy consumption for an underwater sensor network. The optimization algorithm uses the following state parameters to estimate network lifetime: (1) internode distance; (2) transmission frequency; (3) sampling frequency; and (4) number of descendants in the routing tree. Transmissi

带伤害 发表于 2025-3-22 10:20:39

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浅滩 发表于 2025-3-22 13:03:11

B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net

Cubicle 发表于 2025-3-22 18:02:32

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molest 发表于 2025-3-22 23:38:51

B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net

制定法律 发表于 2025-3-23 03:06:13

B. K. Sinha,N. K. Mandal,Manisha Pal,P. Dasases for expanded cross-layer state representations. The experiments also reveal that all state representations in Jurdak’s framework reduce global energy consumption in the range of one-third for a time-driven monitoring network, and in the range of one-fifth for an event-driven target tracking net

Ascendancy 发表于 2025-3-23 08:17:19

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查看完整版本: Titlebook: Optimal Mixture Experiments; B.K. Sinha,N.K. Mandal,P. Das Book 2014 Springer Nature India Private Limited 2014 Bayesian Analysis.Design o