{"id":"W4285099531","doi":"10.18280/jesa.550306","title":"Artificial Techniques Based on Neural Network and Fuzzy Logic Combination Approach for Avoiding Dynamic Obstacles","year":2022,"lang":"en","type":"article","venue":"Journal Européen des Systèmes Automatisés","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Mosul","keywords":"Obstacle; Mobile robot; Obstacle avoidance; Robot; Fuzzy logic; Artificial neural network; Computer science; Artificial intelligence; Control theory (sociology); Simulation; Control engineering; Engineering; Control (management); Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.002089536,0.0002495548,0.0003295237,0.0002986747,0.00193145,0.0005885675,0.0007404915,0.00005707107,0.00000391451],"category_scores_gemma":[0.0002112569,0.0002330368,0.0001160251,0.0005171354,0.00007252071,0.0003829472,0.0002419068,0.0005944187,0.000001768246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003259667,"about_ca_system_score_gemma":0.00008804844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003768285,"about_ca_topic_score_gemma":2.575131e-7,"domain_scores_codex":[0.9971088,0.0008200904,0.000548528,0.000423567,0.0005953644,0.0005036241],"domain_scores_gemma":[0.9984894,0.0004795845,0.0004720904,0.0003155458,0.0001096462,0.00013369],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003965783,0.0002521689,0.0005035622,0.0001078003,0.00003583189,0.0001268871,0.0005689941,0.5109369,0.000524724,0.01405573,0.001131164,0.4717166],"study_design_scores_gemma":[0.0002497055,0.0008169526,0.01405736,0.0000626315,0.00001736553,0.0006378017,0.00007311151,0.9572505,0.00004691445,0.02647591,0.00006315197,0.0002486086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01421795,0.000340257,0.9827146,0.0004926621,0.0006694759,0.0005222409,0.00001101286,0.0005589917,0.0004728372],"genre_scores_gemma":[0.5676807,0.000005477442,0.431778,0.0002603865,0.0001163541,0.00006836317,0.00001116781,0.00002779958,0.00005174924],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5534627,"threshold_uncertainty_score":0.9993679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03218229702032457,"score_gpt":0.2686398953011813,"score_spread":0.2364575982808567,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}