Search Results - (( java implication based algorithm ) OR ( data application bat algorithm ))

Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

“…BAT algorithm uses echolocation technique like bats to generate bat population and random data is generated, the robot then traverses and the distance is calculated which is compared to the distance from the obstacle. …”
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Application of Bat Algorithm and Its Modified Form Trained with ANN in Channel Equalization by Pradyumna Kumar Mohapatra, Saroja Kumar Rout, Sukant Kishoro Bisoy, Sandeep Kautish, Muzaffar Hamzah, Muhammed Basheer Jasser, Ali Wagdy Mohamed

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Naive bayes-guided bat algorithm for feature selection. by Taha, Ahmed Majid, Mustapha, Aida, Chen, Soong Der

“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

“…The Modified Adaptive Bats Sonar Algorithm (MABSA), initially designed for single objective optimization and inspired by colony bats' echolocation, has demonstrated efficiency with its simple structure and reduced computation time. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

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TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

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Naive Bayes-guided bat algorithm for feature selection by Taha A.M., Mustapha A., Chen S.-D.

“…Bio-inspired method called Bat Algorithm hybridized with a Naive Bayes classifier has been presented in this work. …”

Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

Bat algorithm and neural network for monthly streamflow prediction by Zaini N., Malek M.A., Yusoff M., Osmi S.F.C., Mardi N.H., Norhisham S.

“…Two prediction models are proposed in this study which are BPNN and hybrid Bat-BPNN. Monthly historical rainfall data, antecedent river flow data and meteorology parameters data for two different rivers were used as the input to the proposed models. …”

Metaheuristic Algorithms and Neural Networks in Hydrology

“…This book summarizes the latest research and developments related to the application of nature-inspired metaheuristic algorithms coupled with artificial neural networks (ANNs) in hydrology. …”
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Delay and energy-aware routing for efficient data collection in wireless sensor networks / Ihsan Ali by Ihsan , Ali

“…To address relay node selection and data scheduling issues, Energy-Efficient Scheduling (EES) and Energy-Efficient Un-Scheduling (EEUS) methods have been introduced using the Improved Discrete Bat Algorithm (IDBA) along with the Adaptive Warshal Floyd algorithm (AWF). …”
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Dynamic user preference parameters selection and energy consumption optimization for smart homes using deep extreme learning machine and bat algorithm by Shah, Abdul Salam, Mohamad Nasir, Haidawati, Fayaz, Muhammad, Lajis, Adidah, Ullah, Israr, Shah, Asadullah

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Benchmarking of Bat-inspired Interaction Testing Strategy by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B.

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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Thus, it can be concluded that QEEA algorithm is the most energy efficient and the best candidate for provisioning the QoS for the real time (RT) and non-real time (NRT) applications.…”
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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems by Yaseen, Zaher, Ehteram, Mohammad, Hossain, Md., Fai, Chow, Koting, Suhana, Mohd, Nuruol Syuhadaa, Jaafar, Wan Zurina Wan, Afan, Haitham Abdulmohsin, Lai, Sai Hin, Zaini, Nuratiah, Ahmed, Ali, El-Shafie, Ahmed

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Suspended sediment load prediction using artificial neural network and ant lion optimization algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Ebrahimi M., Fai C.M., Huang Y.F., El-Shafie A.

A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems by Yaseen Z.M., Ehteram M., Hossain M.S., Fai C.M., Koting S.B., Mohd N.S., Jaafar W.Z.B., Afan H.A., Hin L.S., Zaini N., Ahmed A.N., El-Shafie A.

The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration by Yaseen, Zaher, Ehteram, Mohammad, Sharafati, Ahmad, Shahid, Shamsuddin, Al-Ansari, Nadhir, El-Shafie, Ahmed

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