Search Results - (( probable distribution control algorithm ) OR ( probable distribution sensor algorithm ))

Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

“…Also, self-adaptive scaling factor and crossover probability control parameters are introduced to diminish time of finding an optimal parameter to produce the best population. …”
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Energy Efficient LEACH (EE-LEACH) Routing Algorithm for Wireless Sensor Networks by Pillay, Kosheila Sundram

“…Therefore, this research work proposes an energy-efficient LEACH (EE-LEACH) algorithm to elect CHs based on residual energy, RSSI, and random probability to distribute the load evenly among the CHs. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

“…Electric transformers; Health; Hidden Markov models; Nonlinear programming; Probability distributions; Quality control; Viterbi algorithm; Condition parameters; Dissolved gas analysis; Distribution transformer; Emission probabilities; Health indices; Non-linear optimization; Remaining useful lives; Transition probabilities; Parameter estimation…”

Recent Efficient Iterative Algorithms on Cognitive Radio Cooperative Spectrum Sensing to Improve Reliability and Performance by Akbari, M., Reza, A.W., Noordin, K.A., Dimyati, K., Manesh, M.R., Hindia, M.N.

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Energy efficient cluster head distribution in wireless sensor networks by Siew, Zhan Wei

“…For network clustering, the distribution of CH selection directly influences the networks lifetime. …”
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Evaluation of MAC's distributed queuing algorithm for Internet of things applications by Agel, Mabruka Mohamed, Habaebi, Mohamed Hadi, Alnahdi, Sameha, Islam, Md. Rafiqul

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Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm by Shalash, Nadheer A., Abu Zaharin, Ahmad

“…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. These agents shall be applied in terms of the loss of load probability (LOLP) and loss of load expectation (LOLE) which when implemented and compared based on a Malaysian distribution network (DISCO-Net). …”
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EFFICIENT DYNAMIC ADDRESSING BASED ROUTING FOR UNDERWATER WIRELESS SENSOR NETWORKS by ARSHAD, MUHAMMAD AYAZ ARSHAD

“…Besides long propagation delays and high error probability, continuous node movement also makes it difficult to manage the routing information during the process of data forwarding. …”
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A new hybrid GA−ACO−PSO algorithm for solving various engineering design problems by Tam, Jun Hui, Ong, Zhi Chao, Ismail, Zubaidah, Ang, Bee Chin, Khoo, Shin Yee

“…The intention of this hybridization is to further enhance the exploratory and exploitative search capabilities involving simple concepts. The proposed algorithm adopts the combined discrete and continuous probability distribution scheme of ant colony optimization (ACO) to specifically assist genetic algorithm in the aspect of exploratory search. …”
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Service and Voltage Sag Study of Humid and Dry Weather Utilities by Khan, Nasrullah, Marion, Norman, Bashi, Sinan Mahmod, Yusuf, Sallehhudin

“…The study has been focused to formulate algorithm for estimating probability of nuisance trip outs in industrial organizations operating in humid and hot dry environments. …”
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Multi-objective scientific workflow scheduling algorithm in multi-cloud environment for satisfying QoS requirements by Ramadhan, Mazen Farid Ebrahim

“…With the MOS-MWO algorithm, makespan is reduced by 40%, cost also reduced by 3 % and risk probability reduced by 86%. …”
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A review on path collisions and resources usage in hybrid optical Network on Chip (HONoC) by Razali R.A., Othman M.

Prediction of rice biomass using machine learning algorithms by Radhwane, Derraz

“…The Q-TESI, C-TESI, and L-TESI overcame the LN-TESI in retaining the features’ original probability distribution, minimising the augmentation loss, reducing the VIF, increasing the rs, and decreasing the DNN under- and overfitting. …”
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Population genetic structure of Malayan Tapir (Tapirus indicus Desmarest) in Peninsular Malaysia by Lim, Qi Luan

“…Using K-means clustering algorithm, five clusters were inferred among the wild samples (N = 57), which showed a complex population structure probably comprising multiple continuous populations that also experiencing considerably restricted gene flow due to isolation by geographical barriers especially mountain ranges. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…In Chapter 4, we propose a fast Distributed Denial of Service (DDoS) backscat�ter detection system to detect DDoS backscatter from a combination of protocols and ports other than the following two labeled packets: Transmission Control Protocol (TCP) Port 80 (80/TCP) and User datagram Protocol (UDP) Port 53 (53/UDP). …”
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